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  • 1
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    Institute of Electrical and Electronics Engineers (IEEE)
    In:  IEEE Transactions on Geoscience and Remote Sensing .
    Publication Date: 2019-01-22
    Description: Underwater hyperspectral imaging is a relatively new method for characterizing seafloor composition. To date, it has been deployed from moving underwater vehicles, such as remotely operated vehicles and autonomous underwater vehicles. While moving vehicles allow relatively rapid surveying of several 10-1000 m², they are subjected to short-term variations in vehicle attitude that often compromise image acquisition and quality. In this study, we tested a stationary platform that was landed on the seabed and used an underwater hyperspectral imager (UHI) on a vertical swinging bracket. The imaged seafloor areas have dimensions of 2.3 m x 1 m and are characterized by very stable UHI data of high spatial resolution. The study area was the Trans-Atlantic Geotraverse hydrothermal field at the Mid-Atlantic Ridge (26° N) in water depths of 3530-3660 m. UHI data were acquired a 12 stations on an active and an inactive hydrothermal sulfide mound. Based on supervised classification, 24 spectrally different seafloor materials were detected, including hydrothermal and non-hydrothermal materials, and benthic fauna. The results show that the UHI data are able to spectrally distinguish different types of surface materials and benthic fauna in hydrothermal areas, and may therefore represent a promising tool for high-resolution seafloor exploration in potential future deep-sea mining areas.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 2
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Print ISSN: 0018-9197
    Electronic ISSN: 1558-1713
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 3
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Print ISSN: 0018-9197
    Electronic ISSN: 1558-1713
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 4
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: Underwater vision suffers from severe effects due to selective attenuation and scattering when light propagates through water. Such degradation not only affects the quality of underwater images, but limits the ability of vision tasks. Different from existing methods that either ignore the wavelength dependence on the attenuation or assume a specific spectral profile, we tackle color distortion problem of underwater images from a new view. In this letter, we propose a weakly supervised color transfer method to correct color distortion. The proposed method relaxes the need for paired underwater images for training and allows the underwater images being taken in unknown locations. Inspired by cycle-consistent adversarial networks, we design a multiterm loss function including adversarial loss, cycle consistency loss, and structural similarity index measure loss, which makes the content and structure of the outputs same as the inputs, meanwhile the color is similar to the images that were taken without the water. Experiments on underwater images captured under diverse scenes show that our method produces visually pleasing results, even outperforms the state-of-the-art methods. Besides, our method can improve the performance of vision tasks.
    Print ISSN: 1070-9908
    Electronic ISSN: 1558-2361
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 5
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Print ISSN: 0196-2892
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  • 6
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Print ISSN: 0018-9197
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  • 7
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: To monitor a space target, 3-D reconstruction from a multiview sequence of the inverse synthetic aperture radar (ISAR) imaging is developed. Scattering of a complex electric-large target, e.g., the ENVISAT satellite model, is numerically calculated, and multiview 2-D ISAR imaging can be simulated. Under the sparse sampling ISAR imaging via compressed sensing, the Kanade-Lucas–Tomasi feature tracker is applied to extraction of target feature points. Then, using the orthographic factorization method, 3-D reconstruction of those feature points is produced. A simple hexagonal frustum is first tested for the feasibility analysis. Two sequences of multiview ISAR imaging, one is the ENVISAT model and another real measurements of a space shuttle, are then presented for 3-D reconstruction. Furthermore, a complex multistructure model of the International Space Station is also studied from multiview ISAR imaging under different sparse sampling rates. All results demonstrate good feasibility of the 3-D reconstruction for those target components, e.g., solar panel and antenna.
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  • 8
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: The performance of scene classification relies heavily on the spatial and structural features that are extracted from high spatial resolution remote-sensing images. Existing approaches, however, are limited in adequately exploiting latent relationships between scene images. Aiming to decrease the distances between intraclass images and increase the distances between interclass images, we propose a latent relationship learning framework that integrates an adaptive graph with the constraints of the feature space and label propagation for high-resolution aerial image classification. To describe the latent relationships among scene images in the framework, we construct an adaptive graph that is embedded into the constrained joint space for features and labels. To remove redundant information and improve the computational efficiency, subspace learning is introduced to assist in the latent relationship learning. To address out-of-sample data, linear regression is adopted to project the semisupervised classification results onto a linear classifier. Learning efficiency is improved by minimizing the objective function via the linearized alternating direction method with an adaptive penalty. We test our method on three widely used aerial scene image data sets. The experimental results demonstrate the superior performance of our method over the state-of-the-art algorithms in aerial scene image classification.
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  • 9
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: In remote sensing image classification, active learning aims to learn a good classifier as best as possible by choosing the most valuable (informative and representative) training samples. Multiview is a concept that regards analyzing the same object from multiple different views. Generally, these views show diversity and complementarity of features. In this paper, we propose a new multiview active learning (MVAL) framework for hyperspectral image classification. First, we generate multiple views by extracting different attribute components from the same image data. Specifically, we adopt the multiple morphological component analysis to decompose the original image into multiple pairs of attribute components, including content , coarseness , contrast , and directionality , and the smooth component from each pair is chosen as one single view. Second, we construct two multiview intensity-based query strategies for active learning. On the one hand, we exploit the intensity differences of multiple views along with the samples’ uncertainty to choose the most informative candidates. On the other hand, we consider the clustering distribution of all unlabeled samples, and query the most representative candidates in addition to the highly informative ones. Our experiments are performed on four benchmark hyperspectral image data sets. The obtained results show that the proposed MVAL framework can lead to better classification performance than the traditional, single-view active learning schemes. In addition, compared with the conventional disagree-based MVAL scheme, the proposed query selection strategies show competitive classification accuracy.
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  • 10
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: Given the improvement of synthetic aperture radar (SAR) imaging technologies, the resolution of SAR image is largely improved and the variation of backscatter amplitude should be considered in SAR image processing. In this paper, considering the spatial geometric properties of SAR image in gray pixel space and the sample selection in the estimation of true signal, local directional property of each pixel is explored with the help of SAR sketching method, and two specially designed filters are integrated for adaptive speckle reduction of SAR images. Specifically, based on the sketch map of a SAR image, the orientation of the sketch point lying at each sketch segment is assigned to the corresponding pixel, and thus all pixels of the SAR image are classified as the directional pixels and the nondirectional pixels. For the directional pixels, given the significant directionality of its neighborhood, a geometric-structural block (GB) is built to center on it and GB-wised nonlocal means filter is designed to estimate the true values of all pixels contained in the GB. Moreover, using the local orientation, the whole image is adopted as the searching range to search the similar GBs. For the nondirectional pixels, based on the locally estimated equivalent number of looks, a novel pixel-based metric is proposed to determine the local adaptive neighborhood (AN) with which an AN-based filter is developed to estimate its true value. Besides, since some nondirectional pixels are contained in GBs, a Bayesian-based fusion strategy is designed for the fusion of their estimated values. In the experiments, three synthetic speckled images and five real SAR images [obtained with different resolutions (e.g., 3, 1, and 0.1 m) and different bands (e.g., X-band, C-band, and Ka-band)] are used for evaluation and analysis. Owing to the usage of local spatial geometric property and the combination of two different filters, the proposed method shows a reas- nable performance among the comparison methods, in terms of the speckle reduction and the details’ preservation.
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  • 11
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: This paper describes an experiment that was carried out in the North Sea off the Sylt island in May 2012 with the aim to study the influence of the maritime boundary layer conditions on the propagation of radar signals under low grazing angle geometry and to establish a sea clutter database at different frequencies with a view to contribute to new sea clutter models. The radar measurements were carried out with the highly versatile radar called MEMPHIS operating in sea configuration at X-, Ka-, and W-band, simultaneously. As concerns the oceanographic and atmospheric characterization, the collection of measurements was done with a sophisticated suite of sensors partly mounted on the research vessel (RV) Elisabeth Mann Borgese (EMB) and onboard different types of buoys, a catamaran, and a tethered balloon. Over a period of four days, a comprehensive and valuable data set was successfully collected including clutter measurements under different geometrical configurations and propagation runs with corner reflectors mounted onboard RV EMB. An insight into the overall approach is given together with many measurement examples for a very detailed oceanographic and meteorological characterization and a vast number of multifrequency radar acquisitions, showing the complexity of different parameters that have to be considered for sensor performance assessment and prediction.
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  • 12
    Publication Date: 2018-01-31
    Description: The TanDEM-X mission is the first free flying bistatic SAR mission. It has the primary objective to generate within a short time frame a global digital elevation model (DEM) of 10-m absolute vertical accuracy and 2-m relative height accuracy. For that, the whole land mass has been mapped at least twice with different baselines. The success of the mission depends on the accuracy of the final DEM and therefore on the reliability of the phase unwrapping (PU) algorithm. Hence, a robust and versatile PU method, which is in accordance with the acquisition concept, is necessary. This paper presents a new method that combines bistatic high-resolution interferometric data in order to perform an accurate PU on a huge amount of data. The dual-baseline PU correction (DB-PUC) framework addresses this challenge by correcting errors that occurred during the single-baseline PU procedure. It benefits from the additional information available through the differential interferogram and the stereo-radargrammetric phase , which are used to correct region-wise the ambiguity bands of the misestimated unwrapped phases to be less sensitive to noise and possible temporal changes. The multilevel of the DB-PUC approach makes it flexible, computationally efficient, and well adapted to deal with the various PU error scenarios. This framework is used operationally for the processing of the data of the TanDEM-X mission.
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  • 13
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: Long integration time (LIT) indicates high resolution and/or large scene for spaceborne synthetic aperture radar (SAR) imaging and also means that the effects, brought by curved orbit, cannot be ignored. In this paper, considering the curved orbit caused by the relative motion between an SAR sensor in orbit and targets on a rotating planetary surface, the impacts of the LIT on the imaging results are discussed in detail. The analysis suggests that the cross-coupling phase is two-dimensional (2-D) with spatial variation. Employing the 2-D Taylor series expansion, the 2-D linear relationships between the spatially variant and invariant coefficients are derived, which are exploited to improve the echo formulation. Then, we apply the keystone transform (KT) to process the LIT spaceborne SAR data. Unlike the traditional application of the KT, our two proposed methods, which operate, respectively, in azimuth time and azimuth frequency domains, can greatly remove the spatially variant cross-coupling phase. Moreover, implementation considerations including the curved orbit of LIT spaceborne SAR, applicability of two methods, postprocessing for topography error compensation, and computational load are discussed. Simulation results verify the effectiveness of the developed focusing approaches.
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  • 14
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: This paper investigated the sensitivity of passive microwave L-band soil moisture (SM) retrieval from multiangle airborne brightness temperature data obtained under morning and afternoon conditions from the National Airborne Field Experiment conducted in southeast Australia in 2006. Ground measurements at a dryland focus farm including soil texture, soil temperature, and vegetation water content were used as ancillary data to drive the retrieval model. The derived SM was then in turn evaluated with the ground-measured near-surface SM patterns. The results of this paper show that the Soil Moisture and Ocean Salinity target accuracy of 0.04 $text{m}^{3}cdot text{m}^{-3}$ for single-SM retrievals is achievable irrespective of the 6 A.M. and 6 P.M. overpass acquisition times for moisture conditions $le 0.15~text{m}^{3}cdot text{m}^{-3}$ . Additional tests on the use of the air temperature as proxy for the vegetation temperature also showed no preference for the acquisition time. The performance of multiparameter retrievals of SM and an additional parameter proved to be satisfactory for SM modeling—independent of the acquisition time—with root-mean-square errors less than 0.06 $text{m}^{3}cdot text{m}^{-3}$ for the focus farm.
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  • 15
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: The cross-track infrared sounder has been operated in the full spectral resolution (FSR) mode since December 4, 2014. To provide the FSR radiance spectra with a spectral resolution of 0.625 cm −1 for all the three bands, a new calibration algorithm has been developed and implemented for operational uses. The algorithm is an improvement over the previous algorithm that had been operationally used until March 2017. Major changes include the calibration equation, self-apodization correction and resampling matrices, and calibration filter. Compared to the previous algorithm, the improvement reduces the calibration inconsistencies among the nine fields of view and between the forward and reverse interferometer sweep directions by up to 0.5 K, and the differences between observed and simulated spectra by up to 0.4 K.
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  • 16
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: Light detection and ranging (lidar)-derived elevation data are commonly subjected to outliers due to the boundaries of occlusions, physical imperfections of sensors, and surface reflectance. Outliers have a serious negative effect on the accuracy of digital elevation models (DEMs). To decrease the impact of outliers on DEM construction, we propose a robust interpolation algorithm of multiquadric (MQ) based on a regularized least absolute deviation (LAD) technique. The objective function of the proposed method includes a regularization-based smoothing term and an LAD-based fitting term, respectively, used to smooth noisy samples and resist the influence of outliers. To solve the objective function of the proposed method, we develop a simple scheme based on the split-Bregman iteration algorithm. Results from simulated data sets indicate that when sample points are noisy or contaminated by outliers, the proposed method is more accurate than the classical MQ and two recently developed robust algorithms of MQ for surface modeling. Real-world examples of interpolating 1 private and 11 publicly available airborne lidar-derived data sets demonstrate that the proposed method averagely produces better results than two promising interpolation methods including regularized spline with tension (RST) and gridded data-based robust thin plate spline (RTPS). Specifically, the image of RTPS is too smooth to retain terrain details. Although RST can keep subtle terrain features, it is distorted by some misclassified object points (i.e., pseudooutliers). The proposed method obtains a good tradeoff between resisting the effect of outliers and preserving terrain features. Overall, the proposed method can be considered as an alternative for interpolating lidar-derived data sets potentially including outliers.
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  • 17
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: When dealing with forest scenario, target scattering separation using synthetic aperture radar (SAR) tomography is a challenging task for the application of biophysical parameter retrieval approaches. One important and widely popular solution used to investigate the scattering mechanism separation based on multipolarimetric multibaseline (MPMB) SAR data is the sum of Kronecker products (SKPs), which provides the basis for decomposition of the data into ground-only and canopy-only contributions. In this paper, we investigate the possibility of characterizing multiple scattering mechanisms using the SKPs of covariance matrix. In particular, we present a method for characterization of forest structure using MPMB data that adapt SKP with the generalized volume description and the physical model of interferometric cross correlation as the sum of scattering contributions. According to the Freeman–Durden model, the method expresses the estimated covariance matrix in terms of the Kronecker product of polarimetric and interferometric coherence matrices corresponding to direct, double-bounce, and random-volume scattering mechanisms. The proposed method is tested with simulated and P-band MB data acquired by ONERA over a tropical forest in French Guiana in the frame of the European Space Agency’s campaign TROPISAR. Comparison of the retrieved height of trees with a LiDAR-based canopy model as a reference showed that the proposed method has the potential to decrease root-mean-square error of forest height by up to 3.9 m with respect to SKP.
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  • 18
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: We focus on the detection of sporadic low-power acoustic/seismic signals of unknown structure and statistics, such as the detection of sound produced by marine mammals, low-power underground signals, or the discovery of events such as volcano eruptions. In these cases, since the ambient noise may be fast time varying and may include many noise transients, threshold-based detection may lead to a significant false alarm rate. Instead, we propose a detection scheme that avoids the use of a decision threshold. Our method is based on clustering the samples of the observed buffer according to a binary hidden Markov model to discriminate between “noise” and “signal” states. Our detector is a modification of the Baum–Welch algorithm that takes into account the expected continuity of the desired signal and obtains a robust detection using the complex but flexible general Gaussian mixture model. The result is a combination of a constrained expectation-maximization algorithm with the Viterbi algorithm. We evaluate the performance of our scheme in numerical simulations, in a seimic test, and in an ocean experiment. The results are close to the hybrid Cramér–Rao lower bound and show that, at the cost of some additional complexity, our proposed algorithm outperforms common benchmark methods in terms of detection and false alarm rates, and also achieves a better accuracy of the time of detection. To allow reproducibility of the results, we publish our code.
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  • 19
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: A new algorithm called the Mondrian detector has been developed for object detection in high-frequency synthetic aperture sonar (SAS) imagery. If a second (low) frequency-band image is available, the algorithm can seamlessly exploit the additional information via an auxiliary prescreener test. This flexible single-band and multiband functionality fills an important capability gap. The algorithm’s overall prescreener component limits the number of potential alarms. The main module of the method then searches for areas that pass a subset of pixel-intensity tests. A new set of reliable classification features has also been developed in the process. The overall framework has been kept uncomplicated intentionally in order to facilitate performance estimation, to avoid requiring dedicated training data, and to permit delayed real-time detection at sea on an autonomous underwater vehicle. The promise of the new algorithm is demonstrated on six substantial data sets of real SAS imagery collected at various geographical sites that collectively exhibit a wide range of diverse seafloor characteristics. The results show that—as with Mondrian’s art—simplicity can be powerful.
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  • 20
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification difficult. Machine-learning classifiers can help at this, and many methods are currently available. A popular kernel classifier is the Gaussian process classifier (GPC), since it approaches the classification problem with a solid probabilistic treatment, thus yielding confidence intervals for the predictions as well as very competitive results to the state-of-the-art neural networks and support vector machines. However, its computational cost is prohibitive for large-scale applications, and constitutes the main obstacle precluding wide adoption. This paper tackles this problem by introducing two novel efficient methodologies for GP classification. We first include the standard random Fourier features approximation into GPC, which largely decreases its computational cost and permits large-scale remote sensing image classification. In addition, we propose a model which avoids randomly sampling a number of Fourier frequencies and alternatively learns the optimal ones within a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery and infrared sounding data. Excellent empirical results support the proposal in both computational cost and accuracy.
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  • 21
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: In [1] , information regarding the corresponding author is missing. The information is updated here. The updated footnote below shows that Xiaoyan Luo is the corresponding author for this paper.
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  • 22
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-01-31
    Description: As one of the most challenging tasks of remote sensing big data mining, large-scale remote sensing image retrieval has attracted increasing attention from researchers. Existing large-scale remote sensing image retrieval approaches are generally implemented by using hashing learning methods, which take handcrafted features as inputs and map the high-dimensional feature vector to the low-dimensional binary feature vector to reduce feature-searching complexity levels. As a means of applying the merits of deep learning, this paper proposes a novel large-scale remote sensing image retrieval approach based on deep hashing neural networks (DHNNs). More specifically, DHNNs are composed of deep feature learning neural networks and hashing learning neural networks and can be optimized in an end-to-end manner. Rather than requiring to dedicate expertise and effort to the design of feature descriptors, we can automatically learn good feature extraction operations and feature hashing mapping under the supervision of labeled samples. To broaden the application field, DHNNs are evaluated under two representative remote sensing cases: scarce and sufficient labeled samples. To make up for a lack of labeled samples, DHNNs can be trained via transfer learning for the former case. For the latter case, DHNNs can be trained via supervised learning from scratch with the aid of a vast number of labeled samples. Extensive experiments on one public remote sensing image data set with a limited number of labeled samples and on another public data set with plenty of labeled samples show that the proposed remote sensing image retrieval approach based on DHNNs can remarkably outperform state-of-the-art methods under both of the examined conditions.
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  • 23
    Publication Date: 2018-01-31
    Description: The Terra and Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) scan mirror reflectance is a function of the angle of incidence (AOI) and was characterized prior to launch by the instrument vendor. The relative change of the prelaunch response versus scan angle (RVS) is tracked and linearly scaled on-orbit using observations at two AOIs of 11.2° and 50.2° corresponding to the moon view and solar diffuser, respectively. As the missions continue to operate well beyond their design life of six years, the assumption of linear scaling between the two AOIs is known to be inadequate in accurately characterizing the RVS, particularly at short wavelengths. Consequently, an enhanced approach of supplementing the on-board measurements with response trends from desert pseudoinvariant calibration sites (PICS) was formulated in MODIS Collection 6 (C6). An underlying assumption for the continued effectiveness of this approach is the long-term (multiyear) and short-term (month to month) stability of the PICS. Previous work has shown that the deep convective clouds (DCC) can also be used to monitor the on-orbit RVS performance with less trend uncertainties compared with desert sites. In this paper, the raw sensor response to the DCC is used to characterize the on-orbit RVS on a band and mirror-side basis. These DCC-based RVS results are compared with those of C6 PICS-based RVS, showing an agreement within 2% observed in most cases. The pros and cons of using a DCC-based RVS approach are also discussed in this paper. Although this reaffirms the efficacy of the C6 PICS-based RVS, the DCC-based RVS approach presents itself as an effective alternative for future considerations. Potential applications of this approach to other instruments, such as Suomi National Polar-orbiting Partnership, Joint Polar Satellite Systems, and Visible Infrared Imaging Radiometer Suite, are also discussed.
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  • 24
    Publication Date: 2018-02-07
    Description: The visualization of carbon fibers polyether ether ketone (PEEK) composite material heating for a grounded coplanar waveguide and a stepped impedance low-pass filter by the thermal camera is performed. The purpose of such visualization is to characterize electromagnetic field influence on the diagonally anisotropic composite material and find out its application opportunity. COMSOL Multiphysics simulation has been done in order to understand heating principles and origin. Experimental results were in a good agreement with simulations and they showed that the characteristics of the microstrip structures can be modulated/tuned by simple rotation of the composite material. Finally, a tunable application by the carbon/PEEK composite material for the microstrip low-pass filter was developed due to the microwave absorption selectivity dependence on the composite material orientation.
    Print ISSN: 0018-9480
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 25
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This paper introduces a method giving dimensions of inline evanescent-mode ridge waveguide bandpass filters. Evanescent mode couplings are evaluated individually, without optimization of the entire filter. This is obtained through an improved network model of the evanescent-mode coupling, together with novel analytical formulas to correct the resonators slope parameters. Unlike prior works based on full-wave optimization of the overall structure, this method is fast and leads to accurate bandwidth results. Several filter examples are included to support the design method. A prototype filter has been manufactured and the RF measurements are in good agreement with theory.
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  • 26
    Publication Date: 2018-02-07
    Description: This paper presents the design and measurements of a 32-Gb/s differential-input differential-output transimpedance amplifier (TIA) employed in dual polarization integrated coherent receivers for 100-Gb Ethernet. A circuit technique is shown that uses a replica TIA to stabilize the operating point of the two shunt-feedback input stages as well as to cancel the dc part of the two complementary input currents and balances their offset. The TIA can be operated in two modes, an automatic gain control mode to retain a good total harmonic distortion (THD) over a wide dynamic range and a manual gain control mode. Electrical as well as optical-electrical characterization of the TIA are presented. It achieves a maximum differential transimpedance of 74 dB $Omega $ , 33 GHz of 3-dB bandwidth, 12.2 pA/ $sqrt {text {Hz}}$ of average input-referred noise current density with the photodiode, 900 mV pp of maximum differential output swing, less than 1% of THD for 600 mV pp differential output swing, and 500 $mu text{A}_{text {pp}}$ differential input current. The linearity of the TIA is furthermore demonstrated with PAM4 measurements at 25 Gbaud. The dual TIA chip is fabricated in a 0.13- $mu text{m}$ SiGe:C BiCMOS technology, dissipates 436 mW of power and occupies 2 mm 2 of area.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: To address the challenging needs of small size, wide bandwidth, and low-frequency applicability, a novel phase shifter implementation is introduced that utilizes tunable active differential inductors within all-pass networks. The inductor tuning is used to achieve phase shifts up to 180°. A switchable active balanced-to-unbalanced transition (balun) circuit is included in front of the all-pass network to complement its phase shift capability by another 180°. In addition, the all-pass network is followed by a variable-gain amplifier to correct for gain variations among the phase shifting states and act as an output buffer. Although active inductors have previously been used in the design of various components, to the best of our knowledge this is the first time that they have been used in an all-pass phase shifter. The approach is demonstrated with an on-chip design and implementation exhibiting wideband performance for S- and L-band applications by utilizing the 0.5- $mu text{m}$ TriQuint pHEMT GaAs monolithic microwave integrated circuits (MMIC) process. Specifically, the presented phase shifter $1 times 3.95~ text {mm}^{2}$ die area and operates within the 1.5–3-GHz band (i.e., 2:1 bandwidth) with 10-dB gain, less than 1.5-dB root-mean-square (rms) gain error and less than 9° rms phase error. Comparison with the state-of-the-art MMIC phase shifters operating in S- and L-bands demonstrates that the presented phase shifter exhibits a remarkable bandwidth performance from a very compact footprint with low-power consumption. Consequently, it presents an alternative for the implementation of wideband phase shifters where all-passive implementations will consume expensive die real estate.
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  • 28
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A self-calibrating transmission-reflection method for extraction of electromagnetic properties of materials from waveguide measurements is proposed. It relies on three measurement steps (thru, empty line, and the same line loaded at any position by the sample) to extract electromagnetic properties. When compared with other nonresonant transmission-reflection methods, it has the following features: 1) it does not require application of any calibration method; 2) it does not need any knowledge of the position of the sample within its cell (position invariant); 3) it determines constitutive parameters of the sample; 4) it is noniterative; and 5) it does not involve any sign ambiguity in determination of constitutive parameters. The method was validated and its accuracy was compared with the accuracy of other methods from measured uncalibrated and calibrated scattering parameters of the polyethylene sample with different lengths (3.85 and 7.70 mm). We also applied our method for extraction of electromagnetic properties of a synthesized magnetic sample from its simulated scattering parameters by using the CST Microwave Studio. Following measurements, simulations, and validation, repeatability and uncertainty analyses were performed to access and improve the accuracy of the proposed method.
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  • 29
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A method is presented to accurately assess the uncertainty of calibrated one-port vector network analyzers (VNAs), using various techniques necessary to minimize systematic errors in the uncertainty analysis. Methods to experimentally quantify connector pin-gap discontinuity errors are presented and validated. Furthermore, we present a simplified equivalent air-line measurement model together with a multivariate optimization algorithm suitable for determining the model parameters. The unique strength of this algorithm is that it only requires two-port scattering parameter data of the airline and avoids extensive dimensional characterization. Experimental verification measurements confirm that a significant enhancement in VNA measurement accuracy is achieved by the combined use of offset discs to avoid measurement reference plane errors together with the air-line model to account for device imperfections. It is proven that using this approach, VNA uncertainty levels can be reached by industrial calibration laboratories that so far only were achievable at national measurement institutes via very extensive and cumbersome mechanical measurements.
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  • 30
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A simple diode-based nonlinear verification device (NVD) design for nonlinear vector network analyzers is presented together with an improved figure of merit (FOM) parameter that is insensitive to impedance match and isolates variation of the device’s nonlinear parameters. The stability over 84 h and load–pull performance of this new design have been evaluated.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Advertisement, IEEE. IEEE Collabratec is a new, integrated online community where IEEE members, researchers, authors, and technology professionals with similar fields of interest can network and collaborate, as well as create and manage content. Featuring a suite of powerful online networking and collaboration tools, IEEE Collabratec allows you to connect according to geographic location, technical interests, or career pursuits. You can also create and share a professional identity that showcases key accomplishments and participate in groups focused around mutual interests, actively learning from and contributing to knowledgeable communities. All in one place! Learn about IEEE Collabratec at ieeecollabratec.org.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Accompanied with the rising popularity of compressed sensing, the Alternating Direction Method of Multipliers (ADMM) has become the most widely used solver for linearly constrained convex problems with separable objectives. In this work, we observe that many existing ADMMs update the primal variable by minimizing different majorant functions with their convergence proofs given case by case. Inspired by the principle of majorization minimization, we respectively present the unified frameworks of Gauss-Seidel ADMMs and Jacobian ADMMs, which use different historical information for the current updating. Our frameworks generalize previous ADMMs to solve the problems with non-separable objectives. We also show that ADMMs converge faster when the used majorant function is tighter. We then propose the Mixed Gauss-Seidel and Jacobian ADMM (M-ADMM) which alleviates the slow convergence issue of Jacobian ADMMs by absorbing merits of the Gauss-Seidel ADMMs. M-ADMM can be further improved by backtracking and wise variable partition. We also propose to solve the multi-blocks problems by Proximal Gauss-Seidel ADMM which is of the Gauss-Seidel type. It convegences for non-strongly convex objective. Experiments on both synthesized and real-world data demonstrate the superiority of our new ADMMs. Finally, we release a toolbox that implements efficient ADMMs for many problems in compressed sensing.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Active learning is an effective way of engaging users to interactively train models for visual recognition more efficiently. The vast majority of previous works focused on active learning with a single human oracle. The problem of active learning with multiple oracles in a collaborative setting has not been well explored. We present a collaborative computational model for active learning with multiple human oracles, the input from whom may possess different levels of noises. It leads to not only an ensemble kernel machine that is robust to label noises, but also a principled label quality measure to online detect irresponsible labelers. Instead of running independent active learning processes for each individual human oracle, our model captures the inherent correlations among the labelers through shared data among them. Our experiments with both simulated and real crowd-sourced noisy labels demonstrate the efficacy of our model.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Direct Sparse Odometry (DSO) is a visual odometry method based on a novel, highly accurate sparse and direct structure and motion formulation. It combines a fully direct probabilistic model (minimizing a photometric error) with consistent, joint optimization of all model parameters, including geometry-represented as inverse depth in a reference frame-and camera motion. This is achieved in real time by omitting the smoothness prior used in other direct methods and instead sampling pixels evenly throughout the images. Since our method does not depend on keypoint detectors or descriptors, it can naturally sample pixels from across all image regions that have intensity gradient, including edges or smooth intensity variations on essentially featureless walls. The proposed model integrates a full photometric calibration, accounting for exposure time, lens vignetting, and non-linear response functions. We thoroughly evaluate our method on three different datasets comprising several hours of video. The experiments show that the presented approach significantly outperforms state-of-the-art direct and indirect methods in a variety of real-world settings, both in terms of tracking accuracy and robustness.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Recognizing human actions from unknown and unseen (novel) views is a challenging problem. We propose a Robust Non-Linear Knowledge Transfer Model (R-NKTM) for human action recognition from novel views. The proposed R-NKTM is a deep fully-connected neural network that transfers knowledge of human actions from any unknown view to a shared high-level virtual view by finding a set of non-linear transformations that connects the views. The R-NKTM is learned from 2D projections of dense trajectories of synthetic 3D human models fitted to real motion capture data and generalizes to real videos of human actions. The strength of our technique is that we learn a single R-NKTM for all actions and all viewpoints for knowledge transfer of any real human action video without the need for re-training or fine-tuning the model. Thus, R-NKTM can efficiently scale to incorporate new action classes. R-NKTM is learned with dummy labels and does not require knowledge of the camera viewpoint at any stage. Experiments on three benchmark cross-view human action datasets show that our method outperforms existing state-of-the-art.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Supervised topic models simultaneously model the latent topic structure of large collections of documents and a response variable associated with each document. Existing inference methods are based on variational approximation or Monte Carlo sampling, which often suffers from the local minimum defect. Spectral methods have been applied to learn unsupervised topic models, such as latent Dirichlet allocation (LDA), with provable guarantees. This paper investigates the possibility of applying spectral methods to recover the parameters of supervised LDA (sLDA). We first present a two-stage spectral method, which recovers the parameters of LDA followed by a power update method to recover the regression model parameters. Then, we further present a single-phase spectral algorithm to jointly recover the topic distribution matrix as well as the regression weights. Our spectral algorithms are provably correct and computationally efficient. We prove a sample complexity bound for each algorithm and subsequently derive a sufficient condition for the identifiability of sLDA. Thorough experiments on synthetic and real-world datasets verify the theory and demonstrate the practical effectiveness of the spectral algorithms. In fact, our results on a large-scale review rating dataset demonstrate that our single-phase spectral algorithm alone gets comparable or even better performance than state-of-the-art methods, while previous work on spectral methods has rarely reported such promising performance.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: In this paper, we present an attribute grammar for solving two coupled tasks: i) parsing a 2D image into semantic regions; and ii) recovering the 3D scene structures of all regions. The proposed grammar consists of a set of production rules, each describing a kind of spatial relation between planar surfaces in 3D scenes. These production rules are used to decompose an input image into a hierarchical parse graph representation where each graph node indicates a planar surface or a composite surface. Different from other stochastic image grammars, the proposed grammar augments each graph node with a set of attribute variables to depict scene-level global geometry, e.g., camera focal length, or local geometry, e.g., surface normal, contact lines between surfaces. These geometric attributes impose constraints between a node and its off-springs in the parse graph. Under a probabilistic framework, we develop a Markov Chain Monte Carlo method to construct a parse graph that optimizes the 2D image recognition and 3D scene reconstruction purposes simultaneously. We evaluated our method on both public benchmarks and newly collected datasets. Experiments demonstrate that the proposed method is capable of achieving state-of-the-art scene reconstruction of a single image.
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  • 39
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
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  • 40
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: The tandem duplication random loss operation (TDRL) is an important genome rearrangement operation in metazoan mitochondrial genomes. A TDRL consists of a duplication of a contiguous set of genes in tandem followed by a random loss of one copy of each duplicated gene. This paper presents an analysis of the combinatorics of TDRLs on circular genomes, e.g., the mitochondrial genome. In particular, results on TDRLs for circular genomes and their linear representatives are established. Moreover, the distance between gene orders with respect to linear TDRLs and circular TDRLs is studied. An analysis of the available animal mitochondrial gene orders shows the practical relevance of the theoretical results.
    Print ISSN: 1545-5963
    Electronic ISSN: 1557-9964
    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
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  • 41
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: In this study, the expected time required to eradicate HIV-1 completely was found as the conditional absorbing time in a finite state space continuous-time Markov chain model. The Markov chain has two absorbing states: one corresponds to HIV eradication and another representing the possible disaster. This method allowed us to calculate the expected eradication time by solving systems of linear equations. To overcome the challenge of huge dimension of the problem, we applied a novel stop and resume technique. This technique also helped to stop the numerical computation whenever we wanted and continue later from that point until the final result was obtained. Our numerical study showed the dependence of the expected eradication time of HIV on the half-life of the latently infected cells and there agreed with the previous studies. The study predicted that when the half-life of the latent cells varied from 4.6 to 60 months, it took a mean 4.97 to 31.04 years with a corresponding standard deviation of 0.64 to 3.99 years to eradicate the latent cell reservoir. It also revealed the crucial dependence of eradication time on the initial number of latently infected cells.
    Print ISSN: 1545-5963
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    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
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  • 42
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein $p$ can be considered as characteristics terms for $p$ , which are highly predictive of the potential functions of $p$ . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category $f$ can be considered as characteristics terms of $f$ . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein $p$ by representing $p$ and each functional category $f$ by a vector of weights. Each weight reflects the degree of association between a c- aracteristic term and $p$ (or a characteristic term and $f$ ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of $p$ by employing random walks with restarts on the mentioned network. The walker is the vector of $p$ . Finally, $p$ is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.
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    Topics: Biology , Computer Science
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  • 43
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of $>60$ in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of $〈1$ percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).
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    Topics: Biology , Computer Science
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based . Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of study in coevolutionary analysis. Although there has been considerable work on planar drawings of tanglegrams, they have not been fully explored as combinatorial objects until recently. In this paper, we describe how many discrete mathematical questions on trees “factor” through a problem on tanglegrams, and how understanding that factoring can simplify analysis. Depending on the problem, it may be useful to consider a unordered version of tanglegrams, and/or their unrooted counterparts. For all of these definitions, we show how the isomorphism types of tanglegrams can be understood in terms of double cosets of the symmetric group, and we investigate their automorphisms. Understanding tanglegrams better will isolate the distinct problems on leaf-labeled pairs of trees and reveal natural symmetries of spaces associated with such problems.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A microcavity laser is reported using dye-doped cholesteric liquid crystals (CLCs) filled in a glass capillary with photo-alignment polyimide films. This laser runs based on the properties that a CLC has a refractive index much higher than that of glass, so whispering-gallery-mode (WGM) laser and distributed-feedback-mode lasers are included in the emission spectrum. We obtain a low threshold energy of $4.5;mu {rm{J}} cdot {rm{puls}}{{rm{e}}^{ - 1}} cdot {rm{m}}{{rm{m}}^{ - 2}}$ , establish the shift of 3.04 nm of the WGMs in the temperature range 43–48 °C, and investigate electric field tunability.
    Electronic ISSN: 1943-0655
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: The transverse focal shift (TFS) is a phenomenon that the maximum of a focused field does not occur at the geometrical focus, but is moved a short distance transversely in the focal plane. In this paper, the TFS of vortex beams in a high numerical aperture system is investigated. Four typical types of incident vortex beams are selected and the intensity distributions and the vortices behaviors in the focal region are discussed analytically and numerically. It is found that there are three main parameters, the topological charge, the initial positions of the vortices, and the semiaperture angle influencing the TFS in different ways, and the TFS even can be observed when the vortices annihilate in the focal plane. Our results also show that the intensity maximum can move from the $y$ -axis, $x$ -axis to the geometrical focus, or move from $+y$ -axis to $-y$ -axis in different cases, which may have implications in optical trapping.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Z-domain model of fiber Bragg grating is developed, and its performance analysis is presented in this letter. The developed mathematical model is used for the evaluation of reflection and transmission response. Spectral characteristics in terms of bandwidth, peak transmittance, and side lobes formation is determined for a model of length 0.84 mm and is found to be in very close agreement with previously published fabrication result. A similar structure with different parameters is considered. The transmission response provides a wide full width half maximum (FWHM) bandwidth of 9.52 nm and a peak transmission of 0.067. The proposed model is extended to determine the transmission response for a very small incidence angle variation. Performance parameters, such as FWHM, stopband width, and optical density, are analyzed. Transmission response of the proposed model for different length combinations is evaluated.
    Print ISSN: 1041-1135
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A novel nanoscale plasmonic resonator system based on metal-dielectric-metal plasmonic waveguide coupled with left- or right-handed sectorial-ring stub resonator is proposed and investigated. The two-dimensional simulation demonstrates that a transmission spectrum with two dips and one peak is achieved in the novel system, whose left- or right-handed resonator is the same effect. The transmission spectrum can be highly tuned by adjusting the refractive index $(n)$ of the dielectric, or the central angle ( $theta$ ) or the outer radius $(R)$ and inner radius $(r)$ of the stub (namely the width ( ${w}_{mathrm{ s}}$ ) or center arc length ( $l_{mathrm{ C}}$ ) of the stub) when the $n$ , ${w}_{mathrm{ s}}$ , and $l_{mathrm{ C}}$ are unfixed, and also can be highly controlled by fixing the $n$ , ${w}_{mathrm{ s}}$ , and $l_{mathrm{ C}}$ with different $theta$ , $R$ , and $r$ . The transmission perform- nce is explained by the resonance condition, which agrees well with the numerical simulation or theoretical calculation. The proposed structure realizes asymmetrical, multiple, and tunable or controllable stub, which can become a novel plasmonic nanofilter or nanosensor. This letter provides a promising application for nanoscale optical devices and integrated optics devices.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Face images captured by surveillance videos usually have limited resolution. Due to resolution mismatch, it is hard to match high-resolution (HR) faces with low-resolution (LR) faces directly. Recently, multidimensional scaling (MDS) has been employed to solve the problem. In this letter, we proposed a more discriminative MDS method to learn a mapping matrix, which projects the HR images and LR images to a common subspace. Our method is discriminative since both interclass distances and intraclass distances are taken into consideration. We add an interclass constraint to enlarge the distances of different subjects in the subspace to ensure discriminability. Besides, we consider not only the relationship of HR–LR images, but also the relationship of HR–HR images and LR–LR images in order to preserve local consistency. Experimental results on FERET, Multi-PIE, and SCface databases demonstrate the effectiveness of our proposed approach.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: In nanophotonics, dielectric lenses are used for in-plane focusing of surface plasmon modes, but there is no control over the diffracted fields and focal length of the lens after it has been fabricated. We introduce a conceptual dielectric lens structure which uses optofluidics to tune the focal length and the diffracted fields of surface plasmon modes. The proposed structure is studied as both converging and diverging lens and its possible applications in SPR microscopy is discussed.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: We consider the problem of signal reconstruction from quadratic measurements that are encoded as $+1$ or $-1$ depending on whether they exceed a predetermined positive threshold or not. Binary measurements are fast to acquire and inexpensive in terms of hardware. We formulate the problem of signal reconstruction using a consistency criterion , wherein one seeks to find a signal that is in agreement with the acquired measurements. To enforce consistency, we construct a convex cost using a one-sided quadratic penalty and minimize it using an iterative accelerated projected gradient-descent technique. The projected gradient-descent (PGD) scheme reduces the cost function in each iteration, whereas incorporating momentum into PGD, notwithstanding the lack of such a descent property , exhibits faster convergence than PGD empirically. We refer to the resulting algorithm as binary phase retrieval (BPR). Considering additive white noise contamination prior to quantization, we also derive the Cramér–Rao Bound (CRB) for the binary encoding model. Experimental results demonstrate that the BPR algorithm yields a signal-to-reconstruction error ratio (SRER) of approximately 25 dB in the absence of noise. In the presence of noise prior to quantization, the SRER is within 2 to 3 dB of the CRB.
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  • 53
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Multi-soliton pulses are studied under small perturbations. By means of mutual information, we show that the nonlinear spectrum becomes correlated when a 64-PSK modulated 2-eigenvalues soliton is perturbed by a small additive white Gaussian noise (AWGN). Transmission over two channels are considered: an AWGN channel (back-to-back scenario) and an ideal optical fiber link with distributed noise. We numerically show that the Jost coefficients ${b}({lambda }_{k})$ are less correlated than the discrete spectral amplitudes ${q}_{d}({lambda }_{k})$ while either of them can be alternatively used for modulation. In both channels, we compare the achievable information rates (AIRs) of joint detection and separate detection if the modulation is over either ${q}_{d}({lambda }_{k})$ or ${b}({lambda }_{k})$ . We show that if the length of the link is relatively short, the separate detection of ${b}({lambda }_{k})$ gives almost the same total information rate as the joint detection of ${b}({lambda }_{k})$ or ${q}_{d}({lambda }_{k})$ . Moreover, the AIRs are compared with one of a first-order soliton with the same modulation.
    Print ISSN: 1041-1135
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  • 54
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: We present a novel Sagnac loop phase-modulated microwave photonic link with a pulsed optical source. Unlike a conventional Sagnac loop, the optical phase offset of the loop can be adjusted to quadrature by applying a synchronized modulation signal to an in-loop phase shifting phase modulator. Thereby, it exemplifies the fundamental RF response. With balanced detection, a proof-of-concept link demonstrated an output noise floor of −164 dBm/Hz, which is ~4 dB above the shot noise floor, and a spurious free dynamic range of 104.8 dB Hz 2/3 .
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  • 55
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: The introduction of small motion techniques such as small angle rotation approximation has enabled the three-dimensional reconstruction from a small motion of a camera, so-called structure from small motion (SfSM). In this letter, we propose a closed-form solution dedicated to the rotation estimation problem in SfSM. We show that our method works with a minimal set of two points, and has mild conditions to produce a unique optimal solution in practice. Also, we introduce a three-step SfSM pipeline with better convergence and faster speed compared to the state-of-the-art SfSM approaches. The key to this improvement is the separated estimation of the rotation with the proposed two-point method in order to handle the bas-relief ambiguity that affects the convergence of the bundle adjustment. We demonstrate the effectiveness of our two-point minimal solution and the three-step SfSM approach in synthetic and real-world experiments under the small motion regime.
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  • 56
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors $mathbf{W}$ and $mathbf{H}$ , for the given input matrix $mathbf{A}$ , such that $mathbf{A}approx mathbf{W}mathbf{H}$ . NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms that iteratively solves alternating non-negative least squares (NLS) subproblems for $mathbf{W}$ and $mathbf{H}$ . It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage- a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.
    Print ISSN: 1041-4347
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  • 57
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This work presents a full two-port, i.e., double input-double output, behavioral modeling approach suitable for radio frequency power amplifiers (PAs) in the presence of dynamic load modulation (DLM). The formulation of the model, based on a first-order approximation of a modified Volterra series, accounts for the nonlinear distortion determined by large-signal operation under mismatched conditions, and also for the memory effects stimulated by a modulated PA input signal, or by the dynamic variations of the PA load. By following an exhaustive procedure defined in the frequency domain, the model of a general purpose commercial PA is extracted over 160 MHz of modulation bandwidth (BW) with nonlinear vector network analyzer measurements. Validation results under 20-MHz BW multisine excitation and injected 80-MHz BW multisine load modulation show improved prediction capabilities with respect to quasi-static or single-input descriptions, allowing for reliable system-level simulations in the presence of DLM.
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  • 58
    Publication Date: 2018-02-07
    Description: This paper presents a new simple model for representing and characterizing the loss effect introduced by the roughness of the metal-to-dielectric interface on the conductor attenuation of substrate integrated waveguides. The proposal allows for the parameter determination using simple linear regressions which can be implemented directly from S-parameter data and avoids the use of data corresponding to structures with perfectly smooth conductors. In fact, no previous knowledge of the metal surface profile is required to obtain the model parameters. Excellent agreement between full-wave simulations and experimental data at several tens of gigahertz is achieved.
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  • 59
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: In this paper, a new design method for bridged-T coil (BTC) is proposed such that it can be made equivalent to two different transmission line sections at two different frequencies. In this way, on-chip dual-band branch-line coupler and dual-band power divider designs with very compact circuit sizes can be made possible through the use of BTCs. Specifically, the proposed 2.45/5.8-GHz dual-band branch-line coupler realized using the integrated passive device (IPD) process features a compact circuit size of only $2.8~text {mm} times 1.4$ mm while the proposed 2.4/5.5-GHz dual-band power divider in IPD exhibits a very small circuit size of only $1.8~text {mm} times 1.7$ mm. To the best of our knowledge, the proposed dual-band branch-line coupler is the smallest one ever reported while the circuit size of the proposed dual-band power divider is comparable to the smallest in the literature.
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  • 60
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: We present the development of a low-loss, high-power, and ferriteless balun that operates over 0.1–1.6 GHz bandwidth. The proposed balun employs a novel compensated circuit, a single quarter-wave semirigid coaxial cable and an on-board inductor on a thermoset ceramic board to achieve high power and ultrawide bandwidth performance. The experimental results show that the balun achieves a measured average insertion loss of less than 0.5 dB and return loss of better than 10 dB from 100 MHz to more than 1.6 GHz. Within the measured bandwidth, the amplitude and phase imbalances are within ±1 dB and ±5°, respectively. Multiphysics analysis and high-power measurements demonstrate that the balun can handle more than 600 W and above at 1.6 GHz. To the best of our knowledge, the reported balun has the highest measured power handling capability per the largest 16:1 bandwidth ratio to date.
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  • 61
    Publication Date: 2018-02-07
    Description: This paper presents the integration of a diplexer with a corporate feed network of a high gain slot array antenna at the Ka-band. A hybrid diplexer-splitter with a novel architecture is proposed to have compatibility for its direct integration with the feed network of the array antenna. A seventh-order hybrid diplexer-splitter is successfully integrated into a corporate feed network of a $16times 16$ slot array antenna. The proposed integrated diplexer-antenna module consists of three distinct metal layers without the need of electrical contacts between the different layers based on the recently introduced gap waveguide technology. The designed module has two channels of 650-MHz bandwidths each with center frequencies 28.21 and 29.21 GHz. The fabricated prototype provides good radiation and input impedance characteristics. The measured input reflection coefficients for both Tx/Rx ports are better than −13 dB with the measured antenna efficiency better than 60% in the designed passband, which includes the losses in the diplexer.
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  • 62
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: A noise match network for the LC -ladder input network of a broadband inductively source-degenerated common-source (CS) field effect transistor (FET) low-noise amplifier (LNA) is established through noise transformation matrix to derive the noise parameters of a broadband LNA. Analytical formulas for the noise factors of a CS FET LNA with a three-section LC-ladder input network are thus obtained based on the design algorithm of optimal noise and input match developed in this paper. Two 3.7–10.5 GHz two-stage LNAs of the same topology are demonstrated using 0.15- $mu text{m}$ pHEMT technology to validate the design methodology. One LNA has all the fully integrated inductors and the other uses two on-chip inductors replaced by two high-Q bondwire inductors for better noise performance. The measurement results show 11-dB power gain with 2.1-dB noise figure for the LNA with the fully integrated inductors and 11-dB power gain with 1.6-dB noise figure for the LNA with two bondwire inductors, respectively.
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  • 63
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This paper presents an in-depth, systematic study of the impact of input and output harmonics in the design of high-efficiency power amplifiers (PAs). The study evaluates the performance of harmonically tuned amplifiers, tackling concurrently both input and output harmonics. The proposed theory starts with deriving an altered input voltage waveform under the impact of input nonlinearity. Intrinsic drain voltage and drain current components are formulated as a function of the conduction angle $alpha $ considering both source and load terminations. Output power and drain efficiency are then computed as a function of input nonlinearity, $alpha $ , and output loading conditions. The derived formulations allow to investigate the design sensitivity to input nonlinearity and its impact on fundamental design space. The impact of source harmonics is evaluated using harmonic source pull under different output loading conditions. Thereafter, PA design and implementation has been carried out using NXP 1.95 mm die to confirm the distinctive behavior of class GF and GF −1 amplifiers with respect to the input harmonic terminations. For practical validation, four different design cases with different second harmonic source impedances are investigated. At 2.6 GHz, drain efficiencies ranging between 76% and 83% were exhibited depending on the source and load harmonic tuning for each design case. Measurement results confirm the theoretical findings reported in this paper.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: In this paper, a broadband continuous-mode Doherty power amplifier (CM-DPA) is realized taking advantage of the noninfinity output impedances of peaking stage. Specifically, the carrier PA of the designed DPA operates in a continuous class-J mode when the peaking PA is in the OFF-state, where the output impedance of the peaking PA has some influences on the carrier PA. When the peaking transistor is in the OFF-state, the load impedance variation of the carrier transistor versus noninfinity peaking impedance is presented in this contribution. The proposed method surmounts the back-off drain efficiency deterioration of DPAs at two side working bands through elaborately processing the noninfinity peaking impedance. This paper also presents a method to derive the required OFF-state output impedance of the peaking stage by the carrier PA in a symmetrical broadband DPA. A broadband CM-DPA working over 1.6–2.7 GHz (bandwidth of 51%) is designed and fabricated for interpreting our theories. The simulated load trajectory of the carrier transistor is in line with the design space of continuous class-J mode. Under continuous wave excitation, experimental results show the drain efficiencies of 46.5%–63.5% at 6-dB output back-off power levels and 56%–75.3% at peaking power levels. The maximum output power of this DPA is 43.8–45.2 dBm with a gain of 9.4–11.5 dB across the whole working band. Furthermore, a 20-MHz LTE modulated signal with a peak-to-average power ratio of 7.4 dB is also applied to the fabricated CM-DPA at 2.2 GHz. At an average output power of 37.5 dBm, measurement results show the adjacent channel power ratios of −30.2 and −50.1 dBc before and after digital predistortion, respectively.
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  • 65
    Publication Date: 2018-02-07
    Description: This paper reports for the first time, the dielectric characterization of a new, electronically tuneable electrochromic (EC) thin-film material over the frequency range 1–67 GHz, at temperatures of 7 °C, 23 °C, and 50 °C. Test cells composed of a microstrip line terminated with coplanar waveguide (CPW) transitions were fabricated to facilitate on-wafer RF measurements and the application of different bias voltages using a standard CPW probe station. A precise curve-fitting technique based on full-wave simulations was used to extract the permittivity and loss tangent values of the material. The validity of the dielectric extraction technique was first demonstrated by employing a known material, silicon dioxide (SiO 2 ). It is shown that the dielectric tunability of the EC material varies between 11.3% (1 GHz) and 7.5% (67 GHz) at 23 °C, and the measured loss tangent varies between 0.012 (OFF, 0 V, state) and 0.025 (ON, 6 V, state). Above room temperature, the devices exhibit higher values of dynamic tunability and a small increase in insertion loss. The results obtained for this first generation of tuneable EC material are encouraging, and many of the dielectric properties are shown to compare favourably with other, more mature bulk tuneable media, such as liquid crystals.
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  • 66
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: With emerging medical, chemical, and biological applications of microwave-microfluidic devices, many researchers desire a fast and accurate calibration that can be achieved in a single connection. However, traditional on-wafer or coaxial calibrations require measurements of several different artifacts to the data prior to measuring the microwave-microfluidic device. Ideally, a single artifact would be able to present different impedance states to correct the vector network analyzer data, minimizing drift and eliminating artifact-to-artifact connection errors. Here, we developed a multistate single-connection calibration that used a coplanar waveguide loaded with a microfluidic channel. We then used measurements of the uncorrected scattering parameters of the coplanar waveguide with the channel empty, filled with deionized water, and filled with 30 w% (30 grams per liter) of saline to construct an eight-term error model and switch-term correction. After correction, the residuals between measured scattering parameters and with the literature-based finite-element simulations were below −40 dB from 100 MHz to 110 GHz. This multistate single-connection calibration is compatible with both wafer-probed and connectorized microwave-microfluidic devices for accurate impedance spectroscopy and materials characterization without the need for multiple device measurements.
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    Publication Date: 2018-02-07
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Advertisement: Members share fascinating first-person stories of technological innovations. Come read and contribute your story.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Print ISSN: 0162-8828
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Video text extraction plays an important role for multimedia understanding and retrieval. Most previous research efforts are conducted within individual frames. A few of recent methods, which pay attention to text tracking using multiple frames, however, do not effectively mine the relations among text detection, tracking and recognition. In this paper, we propose a generic Bayesian-based framework of Tracking based Text Detection And Recognition (T $^2$ DAR) from web videos for embedded captions, which is composed of three major components, i.e., text tracking, tracking based text detection, and tracking based text recognition. In this unified framework, text tracking is first conducted by tracking-by-detection. Tracking trajectories are then revised and refined with detection or recognition results. Text detection or recognition is finally improved with multi-frame integration. Moreover, a challenging video text (embedded caption text) database (USTB-VidTEXT) is constructed and publicly available. A variety of experiments on this dataset verify that our proposed approach largely improves the performance of text detection and recognition from web videos.
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  • 71
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Multi-object tracking has been studied for decades. However, when it comes to tracking pedestrians in extremely crowded scenes, we are limited to only few works. This is an important problem which gives rise to several challenges. Pre-trained object detectors fail to localize targets in crowded sequences. This consequently limits the use of data-association based multi-target tracking methods which rely on the outcome of an object detector. Additionally, the small apparent target size makes it challenging to extract features to discriminate targets from their surroundings. Finally, the large number of targets greatly increases computational complexity which in turn makes it hard to extend existing multi-target tracking approaches to high-density crowd scenarios. In this paper, we propose a tracker that addresses the aforementioned problems and is capable of tracking hundreds of people efficiently. We formulate online crowd tracking as Binary Quadratic Programing. Our formulation employs target's individual information in the form of appearance and motion as well as contextual cues in the form of neighborhood motion, spatial proximity and grouping, and solves detection and data association simultaneously. In order to solve the proposed quadratic optimization efficiently, where state-of art commercial quadratic programing solvers fail to find the solution in a reasonable amount of time, we propose to use the most recent version of the Modified Frank Wolfe algorithm, which takes advantage of SWAP-steps to speed up the optimization. We show that the proposed formulation can track hundreds of targets efficiently and improves state-of-art results by significant margins on eleven challenging high density crowd sequences.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: The objective of this paper is to design an embedding method that maps local features describing an image (e.g., SIFT) to a higher dimensional representation useful for the image retrieval problem. First, motivated by the relationship between the linear approximation of a nonlinear function in high dimensional space and the state-of-the-art feature representation used in image retrieval, i.e., VLAD, we propose a new approach for the approximation. The embedded vectors resulted by the function approximation process are then aggregated to form a single representation for image retrieval. Second, in order to make the proposed embedding method applicable to large scale problem, we further derive its fast version in which the embedded vectors can be efficiently computed, i.e., in the closed-form. We compare the proposed embedding methods with the state of the art in the context of image search under various settings: when the images are represented by medium length vectors, short vectors, or binary vectors. The experimental results show that the proposed embedding methods outperform existing the state of the art on the standard public image retrieval benchmarks.
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  • 73
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: The objective of this work is to detect shadows in images. We pose this as the problem of labeling image regions, where each region corresponds to a group of superpixels. To predict the label of each region, we train a kernel Least-Squares Support Vector Machine (LSSVM) for separating shadow and non-shadow regions. The parameters of the kernel and the classifier are jointly learned to minimize the leave-one-out cross validation error. Optimizing the leave-one-out cross validation error is typically difficult, but it can be done efficiently in our framework. Experiments on two challenging shadow datasets, UCF and UIUC, show that our region classifier outperforms more complex methods. We further enhance the performance of the region classifier by embedding it in a Markov Random Field (MRF) framework and adding pairwise contextual cues. This leads to a method that outperforms the state-of-the-art for shadow detection. In addition we propose a new method for shadow removal based on region relighting. For each shadow region we use a trained classifier to identify a neighboring lit region of the same material. Given a pair of lit-shadow regions we perform a region relighting transformation based on histogram matching of luminance values between the shadow region and the lit region. Once a shadow is detected, we demonstrate that our shadow removal approach produces results that outperform the state of the art by evaluating our method using a publicly available benchmark dataset.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: We propose a novel minimal path method for the segmentation of 2D and 3D line structures. Minimal path methods perform propagation of a wavefront emanating from a start point at a speed derived from image features, followed by path extraction using backtracing. Usually, the computation of the speed and the propagation of the wave are two separate steps, and point features are used to compute a static speed. We introduce a new continuous minimal path method which steers the wave propagation progressively using dynamic speed based on path features . We present three instances of our method, using an appearance feature of the path, a geometric feature based on the curvature of the path, and a joint appearance and geometric feature based on the tangent of the wavefront. These features have not been used in previous continuous minimal path methods. We compute the features dynamically during the wave propagation, and also efficiently using a fast numerical scheme and a low-dimensional parameter space. Our method does not suffer from discretization or metrication errors. We performed qualitative and quantitative evaluations using 2D and 3D images from different application areas.
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  • 75
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Light-field cameras have recently emerged as a powerful tool for one-shot passive 3D shape capture. However, obtaining the shape of glossy objects like metals or plastics remains challenging, since standard Lambertian cues like photo-consistency cannot be easily applied. In this paper, we derive a spatially-varying (SV)BRDF-invariant theory for recovering 3D shape and reflectance from light-field cameras. Our key theoretical insight is a novel analysis of diffuse plus single-lobe SVBRDFs under a light-field setup. We show that, although direct shape recovery is not possible, an equation relating depths and normals can still be derived. Using this equation, we then propose using a polynomial (quadratic) shape prior to resolve the shape ambiguity. Once shape is estimated, we also recover the reflectance. We present extensive synthetic data on the entire MERL BRDF dataset, as well as a number of real examples to validate the theory, where we simultaneously recover shape and BRDFs from a single image taken with a Lytro Illum camera.
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  • 76
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Superpixels are perceptually meaningful atomic regions that can effectively capture image features. Among various methods for computing uniform superpixels, simple linear iterative clustering (SLIC) is popular due to its simplicity and high performance. In this paper, we extend SLIC to compute content-sensitive superpixels, i.e., small superpixels in content-dense regions with high intensity or colour variation and large superpixels in content-sparse regions. Rather than using the conventional SLIC method that clusters pixels in $mathbb {R}^5$ , we map the input image $I$ to a 2-dimensional manifold $mathcal {M}subset mathbb {R}^5$ , whose area elements are a good measure of the content density in $I$ . We propose a simple method, called intrinsic manifold SLIC (IMSLIC), for computing a geodesic centroidal Voronoi tessellation (GCVT)—a uniform tessellation—on $mathcal {M}$ , which induces the content-sensitive superpixels in $I$ . In contrast to the existing algorithms, IMSLIC characterizes the content sensitivity b- measuring areas of Voronoi cells on $mathcal {M}$ . Using a simple and fast approximation to a closed-form solution, the method can compute the GCVT at a very low cost and guarantees that all Voronoi cells are simply connected. We thoroughly evaluate IMSLIC and compare it with eleven representative methods on the BSDS500 dataset and seven representative methods on the NYUV2 dataset. Computational results show that IMSLIC outperforms existing methods in terms of commonly used quality measures pertaining to superpixels such as compactness, adherence to boundaries, and achievable segmentation accuracy. We also evaluate IMSLIC and seven representative methods in an image contour closure application, and the results on two datasets, WHD and WSD, show that IMSLIC achieves the best foreground segmentation performance.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: It is often desirable to be able to recognize when inputs to a recognition function learned in a supervised manner correspond to classes unseen at training time. With this ability, new class labels could be assigned to these inputs by a human operator, allowing them to be incorporated into the recognition function—ideally under an efficient incremental update mechanism. While good algorithms that assume inputs from a fixed set of classes exist, e.g. , artificial neural networks and kernel machines, it is not immediately obvious how to extend them to perform incremental learning in the presence of unknown query classes. Existing algorithms take little to no distributional information into account when learning recognition functions and lack a strong theoretical foundation. We address this gap by formulating a novel, theoretically sound classifier—the Extreme Value Machine (EVM). The EVM has a well-grounded interpretation derived from statistical Extreme Value Theory (EVT), and is the first classifier to be able to perform nonlinear kernel-free variable bandwidth incremental learning. Compared to other classifiers in the same deep network derived feature space, the EVM is accurate and efficient on an established benchmark partition of the ImageNet dataset.
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: This article presents two new deterministic algorithms for constructing consensus trees. Given an input of $k$  phylogenetic trees with identical leaf label sets and $n$  leaves each, the first algorithm constructs the majority rule (+) consensus tree in $O(k n)$ time, which is optimal since the input size is $Omega (k n)$ , and the second one constructs the frequency difference consensus tree in $min lbrace O(k n^{2}), O(k n (k + log ^{2}n))rbrace$ time.
    Print ISSN: 1545-5963
    Electronic ISSN: 1557-9964
    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
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  • 79
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    Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018-02-07
    Description: Parameter estimation from multiple measurement vectors (MMVs) is a fundamental problem in many signal processing applications, e.g., spectral analysis and direction-of-arrival estimation. Recently, this problem has been addressed using prior information in form of a jointly sparse signal structure. A prominent approach for exploiting joint sparsity considers mixed-norm minimization in which, however, the problem size grows with the number of measurements and the desired resolution, respectively. In this work, we derive an equivalent, compact reformulation of the $ell _{2,1}$ mixed-norm minimization problem that provides new insights on the relation between different existing approaches for jointly sparse signal reconstruction. The reformulation builds upon a compact parameterization, which models the row-norms of the sparse signal representation as parameters of interest, resulting in a significant reduction of the MMV problem size. Given the sparse vector of row-norms, the jointly sparse signal can be computed from the MMVs in closed form. For the special case of uniform linear sampling, we present an extension of the compact formulation for gridless parameter estimation by means of semidefinite programming. Furthermore, we prove in this case the exact equivalence between our compact problem formulation and the atomic-norm minimization. Additionally, for the case of irregular sampling or a large number of samples, we present a low complexity, grid-based implementation based on the coordinate descent method.
    Print ISSN: 1053-587X
    Electronic ISSN: 1941-0476
    Topics: Electrical Engineering, Measurement and Control Technology
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  • 80
    Publication Date: 2018-02-07
    Description: Protein-protein interactions (PPIs) play a vital role in the biological processes involved in the cell functions and disease pathways. The experimental methods known to predict PPIs require tremendous efforts and the results are often hindered by the presence of a large number of false positives. Herein, we demonstrate the use of a new Genetic Programming (GP) based Symbolic Regression (SR) approach for predicting PPIs related to a disease. In this case study, a dataset consisting of 135 PPI complexes related to cancer was used to construct a generic PPI predicting model with good PPI prediction accuracy and generalization ability. A high correlation coefficient (CC) magnitude of 0.893, and low root mean square error (RMSE), and mean absolute percentage error (MAPE) values of 478.221 and 0.239, respectively, were achieved for both the training and test set outputs. To validate the discriminatory nature of the model, it was applied on a dataset of diabetes complexes where it yielded significantly low CC values. Thus, the GP model developed here serves a dual purpose: (a) a predictor of the binding energy of cancer related PPI complexes, and (b) a classifier for discriminating PPI complexes related to cancer from those of other diseases.
    Print ISSN: 1545-5963
    Electronic ISSN: 1557-9964
    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
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  • 81
    Publication Date: 2018-02-07
    Description: Recent advances in high-throughput technologies have given rise to collecting large amounts of multidimensional heterogeneous data that provide diverse information on the same biological samples. Integrative analysis of such multisource datasets may reveal new biological insights into complex biological mechanisms and therefore remains an important research field in systems biology. Most of the modern integrative clustering approaches rely on independent analysis of each dataset and consensus clustering, probabilistic or statistical modeling, while flexible distance-based integrative clustering techniques are sparsely covered. We propose two distance-based integrative clustering frameworks based on bi-level and bi-objective extensions of the p-median problem. A hybrid branch-and-cut method is developed to find global optimal solutions to the bi-level p-median model. As to the bi-objective problem, an $varepsilon$ -constraint algorithm is proposed to generate an approximation to the Pareto optimal set. Every solution found by any of the frameworks corresponds to an integrative clustering. We present an application of our approaches to integrative analysis of NCI-60 human tumor cell lines characterized by gene expression and drug activity profiles. We demonstrate that the proposed mathematical optimization-based approaches outperform some state-of-the-art and traditional distance-based integrative and non-integrative clustering techniques.
    Print ISSN: 1545-5963
    Electronic ISSN: 1557-9964
    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE