Neural-network-based transformation for joint compression and discrimination

Lipchen Alex Chan; Sandor Z. Der; Nasser M. Nasrabadi

doi:10.1117/12.382924

14 April 2000 Neural-network-based transformation for joint compression and discrimination

Lipchen Alex Chan, Sandor Z. Der, Nasser M. Nasrabadi

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Proceedings Volume 3962, Applications of Artificial Neural Networks in Image Processing V; (2000) https://doi.org/10.1117/12.382924
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

Due to the proliferation of sensor-platform combinations that are capable of wide area searches, automated target detection has become increasingly important. Most learning- algorithm-based target detectors perform dimensionality reduction before actual training, because the high dimensionality of imagery requires enormous training sets to achieve satisfactory performance. One potential problem with this approach is that most dimensionality reduction techniques, such as principal component analysis, seek to maximize the representation of data variation into each component in turn, without considering interclass discriminability. We present a neural-network-based transformation that provides dimensionality reduction and a high degree of discriminability. Our approach achieves simultaneous data compression and target discriminability by adjusting the pretrained base components to maximize separability between classes. This will allow classifiers to operate at a higher level of efficiency and generalization capability on the low-dimensionality data that contain highly discriminative information as well.

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Lipchen Alex Chan, Sandor Z. Der, and Nasser M. Nasrabadi "Neural-network-based transformation for joint compression and discrimination", Proc. SPIE 3962, Applications of Artificial Neural Networks in Image Processing V, (14 April 2000); https://doi.org/10.1117/12.382924

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KEYWORDS

Principal component analysis

Target detection

Sensors

Detection and tracking algorithms

Target recognition

Automatic target recognition

Image processing

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