An improved YOLOv8s-based fish target detection algorithm for marine pasture

Shuchang Wang; Meiqing Xu; Jianwei Yu; Chao Deng; Zixuan Xie; Kai Zheng

doi:10.1117/12.3041997

10 September 2024 An improved YOLOv8s-based fish target detection algorithm for marine pasture

Shuchang Wang, Meiqing Xu, Jianwei Yu, Chao Deng, Zixuan Xie, Kai Zheng

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132571A (2024) https://doi.org/10.1117/12.3041997
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

Marine pasture, a novel technology for ecological balance and sustainable development, heavily relies on cage farming which is typically in deep, complex sea environments, challenging existing fish detection algorithms. Therefore,this paper presents an automatic, cost-effective fish detection system with high precision. By integrating the CBAM attention mechanism, the network's feature perception is enhanced, and the MPDIoU loss function augments small target detection. Trained on fish datasets, the refined YOLOv8s algorithm achieves an mAP of 85.12%, Precision of 80.66%, and Recall of 90.11%, outperforming the standard YOLOv8s with a 0.88% increase in mAP and 1.24% in Recall, deserving being considered for marine fish object detection.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shuchang Wang, Meiqing Xu, Jianwei Yu, Chao Deng, Zixuan Xie, and Kai Zheng "An improved YOLOv8s-based fish target detection algorithm for marine pasture", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132571A (10 September 2024); https://doi.org/10.1117/12.3041997

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