Application of minimum error neural network (MENN) method to target recognition

Weiping Yang; Zhenkang Shen; Zhiyong Li; Hai-Xin Shen

doi:10.1117/12.186594

21 September 1994 Application of minimum error neural network (MENN) method to target recognition

Weiping Yang, Zhenkang Shen, Zhiyong Li, Hai-Xin Shen

Proceedings Volume 2298, Applications of Digital Image Processing XVII; (1994) https://doi.org/10.1117/12.186594
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

In this paper, we introduce a neural network recognition method, MENN (minimum error neural network) method, in target recognition. From the target gray sequences, we can extract some useful characteristics. Then we use these features as the input data of the MENN classifier. By these characteristics, using the MENN classifier we can easily pick out the true targets from the candidate target sequences. MENN recognition method can not only pick out the true target and reject the false targets, but it also gets rid of the baits. Therefore, it has high reliability. Moreover, it has many advantages, for example, its training is a one pass process, its test process is not only simple but also straightforward, and its calculation is simple, etc. On account of those advantages, MENN recognition method is adaptive to the need of realtime processing.

Citation Download Citation

Weiping Yang, Zhenkang Shen, Zhiyong Li, and Hai-Xin Shen "Application of minimum error neural network (MENN) method to target recognition", Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); https://doi.org/10.1117/12.186594

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