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  • Other Sources  (4)
  • Earth Resources and Remote Sensing  (2)
  • BEHAVIORAL SCIENCES  (1)
  • CYBERNETICS  (1)
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    Autoclass: An automatic classification system (1991)
    In:  CASI
    Details
    Publication Date: 2013-08-31
    Description: The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework, and using various mathematical and algorithmic approximations, the AutoClass System searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit, or share, model parameters through a class hierarchy. The mathematical foundations of AutoClass are summarized.
    Keywords: CYBERNETICS
    Type: NASA, Washington, Technology 2001: The Second National Technology Transfer Conference and Exposition, Volume 1; p 442-450
    Format: application/pdf
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    NASA TECHNICAL REPORTS
  • 2
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    Intermodal transfer in temporal discrimination (1975)
    In:  Other Sources
    Details
    Publication Date: 2019-06-27
    Description: This study determined if training for accuracy in temporal discrimination would transfer across sensory modalities. A fractionation method was used in which subjects bisected the durations of acoustic and visual signals at three standard intervals (6, 12, and 18 sec). Absolute error was the performance index. Half of the subjects were trained with acoustic stimuli and then tested in vision; the remainder were trained in vision and tested in audition. Similar negatively accelerated acquisition functions were noted for both modalities. Positive intermodal transfer, characterized by symmetry across modalities, was obtained at all standard durations. The results were considered to provide support for the notion that a common mechanism underlies temporal discriminations in different sensory systems.
    Keywords: BEHAVIORAL SCIENCES
    Type: Perception and Psychophysics; 18; 4, Oc; Oct. 197
    Format: text
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    NASA TECHNICAL REPORTS
  • 3
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    Retrieval of Aerosol Vertical Profiles Using the Oxygen A-Band (2016)
    In:  Other Sources
    Details
    Publication Date: 2020-01-07
    Description: No abstract available
    Keywords: Earth Resources and Remote Sensing
    Type: JPL-CL-16-2915 , Workshop on Remote sensing in the O2 A-band; Jul 08, 2016; De Bilt; Netherlands
    Format: text
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    NASA TECHNICAL REPORTS
  • 4
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    An Improved Automatic Classification of a Landsat/TM Image from Kansas (FIFE) (1994)
    In:  CASI
    Details
    Publication Date: 2019-07-10
    Description: This research note shows the results of applying a new massively parallel version of the automatic classification program (AutoClass IV) to a particular Landsat/TM image. The previous results for this image were produced using a "subsampling" technique because of the image size. The new massively parallel version of AutoClass allows the complete image to be classified without "subsampling", thus yielding improved results. The area in question is the FIFE study area in Kansas, and the classes AutoClass found show many interesting subtle variations in types of ground cover. Displays of the spatial distributions of these classes make up the bulk of this report. While the spatial distribution of some of these classes make their interpretation easy, most of the classes require detailed knowledge of the area for their full interpretation. We hope that some who receive this document can help us in understanding these classes. One of the motivations of this exercise was to test the new version of AutoClass (IV) that allows for correlation among the variables within a class. The scatter plots associated with the classes show that this correlation information is important in separating the classes. The fact that the spatial distribution of each of these classes is far from uniform, even though AutoClass was not given information about positions of pixels, shows that the classes are due to real differences in the image.
    Keywords: Earth Resources and Remote Sensing
    Type: FIA-94-01
    Format: text
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    NASA TECHNICAL REPORTS
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