基于神经网络的声纳系统在鱼类分类中的潜力

[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering Pub Date : 1991-08-15 DOI:10.1109/ICNN.1991.163352

P. Patrick, N. Ramani, W.G. Hanson, H. Anderson

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引用次数: 7

摘要

作者探索了一种基于神经网络的系统的潜力，用于从声纳回波中检测和分类鱼类。初步结果令人鼓舞;一个简单的神经网络能够识别多达86%的测试样本。当识别问题被分成三个子问题时，超过93%的样本被正确识别。这种成功率被发现优于判别分析和最近邻技术。讨论了今后的研究工作

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

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.<>

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[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering

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