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Implementation of Fish Detection Based on Convolutional Neural Networks  

Lee, Yong-Hwan (Dept. of Digital Contents, Wonkwang University)
Kim, Heung-Jun (Dept. of Computer Science and Engineering, Gyeongnam National University of Science and Technology)
Publication Information
Journal of the Semiconductor & Display Technology / v.19, no.3, 2020 , pp. 124-129 More about this Journal
Abstract
Autonomous underwater vehicle makes attracts to many researchers. This paper proposes a convolutional neural network (CNN) based fish detection method. Since there are not enough data sets in the process of training, overfitting problem can be occurred in deep learning. To solve the problem, we apply the dropout algorithm to simplify the model. Experimental result showed that the implemented method is promising, and the effectiveness of identification by dropout approach is highly enhanced.
Keywords
Fish Detection; Object Tracking; Deep Learning; Convolutional Neural Networks;
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