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| Multi-dimensional deep-sea fish recognition algorithm |
| 1. Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000, China； 2. School of Ocean and Earth Science, Tongji University, Shanghai 200092, China |
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Abstract To solve the difficulty of fish recognition and detection due to the nonuniformly distributed deep-sea light,the multi-dimensional deep-sea fish recognition algorithm was proposed based on visual cognition. The traditional GMM was optimized to initially determine the changing area from time dimension and construct the target features from space dimension for extracting the moving target completely. The fish recognition framework based on deep learning was established from spatio-temporal correlation dimension. The results show that the proposed algorithm can accurately extract moving objects under variously complex conditions. The AOM is more than 80%, which is better than that of current mainstream algorithms.
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Received: 27 February 2020
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2021, Vol. 42 
