Article details

Title: More Efficient ATR System Using a New Neural Classification Chain
Author(s): Constantin-Iulian Vizitiu   Stelian Spînu   Grigore Jeler         

Abstract: One of the most important methods to improve the quality of the recognition function assigned to modern automatic target recognition (ATR) systems is to use, in a proper way, new powerful artificial neural architectures in the classification chain. Consequently, an improved neural classification chain using a new procedure for pattern feature extraction, a generalized version of Sammon projection algorithm, and a genetic algorithm to increase the performances of RBF neural networks are proposed. To confirm the broached theoretical aspects, a real image database is used.

Keywords: ATR system, feature extraction and selection, genetic algorithm, RBF neural network.

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