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http://dx.doi.org/10.9723/jksiis.2020.25.4.029

A Study of Active Pulse Classification Algorithm using Multi-label Convolutional Neural Networks  

Kim, Guenhwan (경북대학교 전자공학부)
Lee, Seokjin (경북대학교 전자공학부)
Lee, Kyunkyung (경북대학교 전자공학부)
Lee, Donghwa (대구대학교, ICT융합학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.4, 2020 , pp. 29-38 More about this Journal
Abstract
In this research, we proposed the active pulse classification algorithm using multi-label convolutional neural networks for active sonar system. The proposed algorithm has the advantage of being able to acquire the information of the active pulse at a time, unlike the existing single label-based algorithm, which has several neural network structures, and also has an advantage of simplifying the learning process. In order to verify the proposed algorithm, the neural network was trained using sea experimental data. As a result of the analysis, it was confirmed that the proposed algorithm converged, and through the analysis of the confusion matrix, it was confirmed that it has excellent active pulse classification performance.
Keywords
Active Sonar; Pulse Classification; Convolutional Neural Networks; Multi-Label;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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