Open Access
Error estimation and separability measures in feature selection for multiclass pattern recognition.
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The article was published on 1977-01-01 and is currently open access. It has received 19 citations till now. The article focuses on the topics: Pattern recognition (psychology) & Feature selection.read more
Citations
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Hyperspectral Imaging System Modeling
John P. Kerekes,Jerrold E. Baum +1 more
TL;DR: An analytical end-to-end model that forecasts remote sensing system performance is developed and example parameter trade studies are provided to show the utility of the model for system design and sensor operation applications.
Journal Article
Spectral imaging system analytical model for subpixel object detection
John P. Kerekes,Jerrold E. Baum +1 more
TL;DR: This paper extends an end-to-end remote sensing system modeling approach to subpixel object detection applications by including a linear mixing model for an unresolved object in a background and using object detection algorithms and probability of detection versus false alarm curves to characterize performance.
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Spectral imaging system analytical model for subpixel object detection
John P. Kerekes,Jerrold E. Baum +1 more
TL;DR: In this article, an end-to-end remote sensing system modeling approach was developed to study system parameters in the context of land cover classification, including a linear mixing model for an unresolved object in a background and using object detection algorithms and probability of detection (P/sub D/) versus false alarm (P /sub FA/) curves to characterize performance.
Journal ArticleDOI
Noise in Remote-Sensing Systems: The Effect on Classification Error
David A. Landgrebe,Erick Malaret +1 more
TL;DR: Several types of noise in remote-sensing systems are treated to provide enhanced understanding of the relationship of noise sources to both analysis results and sensor design, including how sensor noise interacts with atmospheric effects to degrade accuracy.
Journal Article
An analytical model of Earth-observational remote sensing systems
TL;DR: Key results include interrelations between the atmosphere, sensor noise, sensor view angle and scattered path radiance and their influence on classification accuracy of the ground cover type and the tradeoffs in ground cell size and surface spatial correlation.
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Feature selection techniques with class separability for multivariate time series
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