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Heng Wang, Pu Zhang, Mengnan You and Xinyuan You
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Zhaoxin Yue, Bing Yan, Huaizhi Liu and Zhe Chen
Underwater creatures play a vital role in maintaining the delicate balance of the ocean ecosystem. In recent years, machine learning methods have been developed to identify underwater biologicals in the complex underwater environment. However, the scarci...
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Jacques Bezuidenhout, Rikus R. le Roux and Kennedy K. Kilel
Sedimentation can cause numerous problems in rivers, estuaries, harbors, and coastal areas. It is therefore important to trace and model the movement of sediments. The natural physical, chemical, and biological components of the aquatic sediment generall...
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Zheng Liu, Yaoming Zhuang, Pengrun Jia, Chengdong Wu, Hongli Xu and Zhanlin Liu
For aquaculture resource evaluation and ecological environment monitoring, the automatic detection and identification of marine organisms is critical; however, due to the low quality of underwater images and the characteristics of underwater biological d...
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Aolun Li, Long Yu and Shengwei Tian
Due to the influence of underwater visual characteristics on the observation of underwater creatures, the traditional object detection algorithm is ineffective. In order to improve the robustness of underwater biological detection, based on the YOLOv4 de...
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Peng Li, Yibing Fan, Zhengyang Cai, Zhiyu Lyu and Weijie Ren
Marine biological object detection is of great significance for the exploration and protection of underwater resources. There have been some achievements in visual inspection for specific objects based on machine learning. However, owing to the complex i...
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Yuanjian Han, Hailong Wu, Jiegang Peng and Bin Ou
Biologists have discovered a kind of weakly electric fish that identifies its prey by using active electrolocation in virtual darkness. In this study, we built an underwater active electrolocation system platform designed to investigate the biological me...
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