Target classification in an optical/digital hybrid neural processor

YanXin Zhang; Zhanbing Feng; Yuhua Li; Jianwen Yang; Shengquan Gao

doi:10.1117/12.234252

4 March 1996 Target classification in an optical/digital hybrid neural processor

YanXin Zhang, Zhanbing Feng, Yuhua Li, Jianwen Yang, Shengquan Gao

Proceedings Volume 2664, Applications of Artificial Neural Networks in Image Processing; (1996) https://doi.org/10.1117/12.234252
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

Abstract

A programmable and reconfigurable optical/digital hybrid neural processor with 1024 neurones is described. The relatively large scale and flexibility of the processor benefit by the mutual complement of the optics and an on-line microcomputer. As an example of application, a target classification of 4 kinds of aircraft based on their binary images rotated in a plane by arbitrary angles is performed. The model is a cascaded neural network consisting of three subnets. The principle of the classifier and computer simulation are outlined. In the preliminary experiments, more than 89% of the unlearned images and imperfect ones can be classified correctly.

Citation Download Citation

YanXin Zhang, Zhanbing Feng, Yuhua Li, Jianwen Yang, and Shengquan Gao "Target classification in an optical/digital hybrid neural processor", Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); https://doi.org/10.1117/12.234252

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