The potential of a neural network based sonar system in classifying fish

Abstract

The authors explore the potential of a neural network based system for detecting and classifying fish from sonar echo returns. Preliminary results are encouraging; a simple neural network was able to identify up to 86% of the test samples. When the identification problem was divided into three subproblems, over 93% of the samples were identified correctly. This success rate was found to be superior to both discriminant analysis and nearest neighbor techniques. Future research activities are discussed.<>