Position-invariant target detection by a neural net

Jon P. Davis; William A. Schmidt

doi:10.1117/12.21163

1 August 1990 Position-invariant target detection by a neural net

Jon P. Davis, William A. Schmidt

Proceedings Volume 1294, Applications of Artificial Neural Networks; (1990) https://doi.org/10.1117/12.21163
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

We investigated the possibility of using an artificial neural network as a translation invariant target detector. The one-dimensional target detection model was a linear array of 20 pixels of which three were unity and the remainder were zero. Several multi-layer back progagation networks were able to distinguish a target consisting of three contiguous pixels from a nontarget three non-contiguous pixels. Under-constrained models were not trainable. A detailed analysis was done of one network with a small number of connections. The network solution appeared to be similar to a triplet correlat ion funct ion. 1.

Citation Download Citation

Jon P. Davis and William A. Schmidt "Position-invariant target detection by a neural net", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21163

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