Research on lightweight fish detection algorithm based on improved YOLOv8n

Minghui Wang; Yan Chen; Liwei Kou; Yinke Dou

doi:10.1117/12.3048079

3 October 2024 Research on lightweight fish detection algorithm based on improved YOLOv8n

Minghui Wang, Yan Chen, Liwei Kou, Yinke Dou

Author Affiliations +

Proceedings Volume 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024); 132720K (2024) https://doi.org/10.1117/12.3048079
Event: 5th International Conference on Computer Vision and Data Mining (ICCVDM 2024), 2024, Changchun, China

Abstract

At present, the polar region is used to monitor and investigate fish by combining sonar detection with artificial fishing statistics, which is limited by economic cost, operation area and time. Object detection algorithms based on deep learning can identify and detect fish while meeting economic requirements, but traditional object detection algorithms often have many parameters and calculations and cannot adapt to the harsh conditions of energy consumption and storage limitations in the polar region. To solve this problem, an improved lightweight fish detection algorithm for YOLOv8n was proposed, in which the GhostC2f module was used to replace C2f in the backbone and neck networks, and GhostConv was used to replace part of the Conv in the network, and the EMA attention mechanism was introduced in the backbone network to improve the feature extraction ability. Finally, the MPDIOU loss function, which is simpler in the calculation process, was used to replace the CIOU to improve the detection speed. Experiments on the self-made fish dataset show that the number of parameters and computation of the improved algorithm become 1.49M and 4.7GFLOPs, respectively, and only 49.67% of the parameters of the original YOLOv8n are used to achieve the same detection accuracy, which meets the requirements of model deployment under limited hardware conditions.

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

Citation Download Citation

Minghui Wang, Yan Chen, Liwei Kou, and Yinke Dou "Research on lightweight fish detection algorithm based on improved YOLOv8n", Proc. SPIE 13272, Fifth International Conference on Computer Vision and Data Mining (ICCVDM 2024), 132720K (3 October 2024); https://doi.org/10.1117/12.3048079

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KEYWORDS

Object detection

Detection and tracking algorithms

Neck

Convolution

Education and training

Feature extraction

Ablation

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