Artificial neural networks for automatic target recognition

The Self Adaptive Hierarchical Target Identification and Recognition Neural Network (SAHTIRN) is a unique and powerful combination of state-of-the-art neural network models for automatic target recognition applications. It is a combination of three modes: (1) an early vision segmentor based on the C...

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Bibliographic Details
Published in:Optical Engineering 1992-12, Vol.31 (12), p.2521-2531
Main Authors: Daniell, Cindy E, Kemsley, David, Lincoln, William P, Tackett, Walter A, Baraghimian, Gregory A
Format: Article
Language:English
Subjects:
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Imaging and optical processing
Optics
Physics
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Summary:The Self Adaptive Hierarchical Target Identification and Recognition Neural Network (SAHTIRN) is a unique and powerful combination of state-of-the-art neural network models for automatic target recognition applications. It is a combination of three modes: (1) an early vision segmentor based on the Canny edge detector, (2) a hierarchical feature extraction and pattern recognition system based on a modified Neocognitron architecture, and (3) a pattern classifier based on the back-propagation network. End-to-end system results from these experiments are provided and interim results from each stage of the SAHTIRN system are discussed. (Author)
ISSN:0091-3286
1560-2303
DOI:10.1117/12.60744