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CNN 기반의 물고기 탐지 알고리즘 구현Implementation of Fish Detection based on Convolutional Neural Networks
- Other Titles
- Implementation of Fish Detection based on Convolutional Neural Networks
- Issue Date
- Sep-2020
- Publisher
- 한국반도체디스플레이기술학회
- Keywords
- Fish Detection; Object Tracking; Deep Learning; Convolutional Neural Networks
- Citation
- 반도체디스플레이기술학회지, v.19, no.3, pp 124 - 129
- Pages
- 6
- Indexed
- KCI
- Journal Title
- 반도체디스플레이기술학회지
- Volume
- 19
- Number
- 3
- Start Page
- 124
- End Page
- 129
- ISSN
- 1738-2270
- 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.
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