1 August 1990 Position-invariant target detection by a neural net
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jon P. Davis, Jon P. Davis, William A. Schmidt, William A. Schmidt, } "Position-invariant target detection by a neural net", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21163; https://doi.org/10.1117/12.21163
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