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    MDPI - Multidisciplinary Digital Publishing Institute
    Publication Date: 2024-04-11
    Description: This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
    Keywords: TA1-2040 ; T1-995 ; similarity measure ; information filter ; out-of-sequence ; Hellinger distance ; coefficient of determination maximization strategy ; uncertainty measure ; embedded systems ; Internet of things (IoT) ; random delays ; adaptive distance function ; random finite set ; Dempster–Shafer evidence theory (DST) ; safe trajectory ; health reliability degree ; dynamic optimization ; state probability approximation ; sensors bias ; multi-environments ; belief entropy ; quaternion ; closed world ; Gaussian process regression ; Gaussian mixture model (GMM) ; intelligent transport system ; multirotor UAV ; multi-sensor system ; attitude ; time-domain data fusion ; precision landing ; Industry 4.0 ; magnetic angular rate and gravity (MARG) sensor ; uncertainty ; unscented information filter ; data classification ; high-definition map ; global information ; inconsistent data ; extended belief entropy ; sensor system ; Steffensen’s iterative method ; SLAM ; the Range-Range-Range frame ; evidential reasoning ; belief functions ; powered two wheels (PTW) ; electronic nose ; particle swarm optimization ; grey group decision-making ; user experience platform ; complex surface measurement ; DoS attack ; extended Kalman filter ; ICP ; Gaussian density peak clustering ; artificial marker ; random parameter matrices ; optimal estimate ; local structure descriptor ; object classification ; domain adaption ; networked systems ; expectation maximization (EM) algorithm ; attitude estimation ; Gaussian process model ; least-squares smoothing ; target positioning ; RFS ; spectral clustering ; maintenance decision ; multi-target tracking ; GMPHD ; time-distributed ConvLSTM model ; non-rigid feature matching ; unknown inputs ; cardiac PET ; subspace alignment ; gradient domain ; multi-sensor measurement ; data fusion ; Bar-Shalom Campo ; Kalman filter ; signal feature extraction methods ; sensor data fusion algorithm ; distributed architecture ; predictive modeling techniques ; Gaussian mixture model ; self-reporting ; deep learning ; mutual support degree ; security zones ; sensor array ; soft sensor ; aircraft pilot ; projection ; vehicle-to-everything ; distributed intelligence system ; square-root cubature Kalman filter ; information fusion ; evidence combination ; LiDAR ; feature representations ; multi-sensor information fusion ; linear constraints ; galvanic skin response ; decision-level sensor fusion ; most suitable parameter form ; Pignistic vector angle ; SINS/DVL integrated navigation ; fault diagnosis ; facial expression ; yaw estimation ; dual gating ; multi-sensor data fusion ; multisensor system ; A* search algorithm ; data fusion architectures ; drift compensation ; augmented state Kalman filtering (ASKF) ; manifold ; nested iterative method ; data preprocessing ; interference suppression ; conflicting evidence ; sonar network ; Gaussian process ; health management decision ; state estimation ; eye-tracking ; high-dimensional fusion data (HFD) ; MEMS accelerometer and gyroscope ; multitarget tracking ; gaussian mixture probability hypothesis density ; integer programming ; image registration ; Dempster–Shafer evidence theory ; linear regression ; data association ; nonlinear system ; covariance matrix ; multi-source data fusion ; fuzzy neural network ; least-squares filtering ; fire source localization ; network flow theory ; weight maps ; camera ; plane matching ; calibration ; unmanned aerial vehicle ; fixed-point filter ; workload ; intelligent and connected vehicles ; mimicry security switch strategy ; alumina concentration ; the Range-Point-Range frame ; spatiotemporal feature learning ; distributed fusion ; user experience evaluation ; image fusion ; vehicular localization ; sensor fusion ; vibration ; parameter learning ; weighted fusion estimation ; data registration ; pose estimation ; surface quality control ; trajectory reconstruction ; land vehicle ; square root ; Deng entropy ; multi-focus ; EEG ; low-cost sensors ; sensor fusing ; sensor data fusion ; packet dropouts ; estimation ; industrial cyber-physical system (ICPS) ; multi-sensor time series ; multi-sensor network ; Human Activity Recognition (HAR) ; transfer ; multisensor data fusion ; convergence condition ; interaction tracker ; acoustic emission ; Covariance Projection method ; mix-method approach ; orthogonal redundant inertial measurement units ; sematic segmentation ; Surface measurement ; conflict measurement ; user experience measurement ; observable degree analysis ; open world ; novel belief entropy ; cutting forces ; machine health monitoring ; Bayesian reasoning method ; orientation ; surface modelling ; hybrid adaptive filtering ; supervoxel ; RTS smoother ; Dempster-Shafer evidence theory (DST) ; fast guided filter. ; multi-sensor joint calibration ; principal component analysis ; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
    Language: English
    Format: application/octet-stream
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