Application of optimized deformable convolution in underwater biological detection algorithm

Hongwei Zhuang; Weisheng Liu

doi:10.1117/12.3034892

11 July 2024 Application of optimized deformable convolution in underwater biological detection algorithm

Hongwei Zhuang, Weisheng Liu

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132102V (2024) https://doi.org/10.1117/12.3034892
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

Underwater target detection is an important method for marine life detection. However, the accuracy of target detection and recognition is affected by the problems of image occlusion, blurred water quality and complex background of underwater targets. An improved YOLOV7 underwater biological target detection method is proposed to address the above problems. Firstly, the DCN structure is improved by incorporating the residual structure into the DCN, with new jump connections and 1×1 convolutional branches, so that the network can learn the residual information between the input and the output. It can improve the expressive ability of the model, reduce the number of parameters, and enhance the adaptability to the shape of the object. Finally, COT3 is integrated, which utilises a self-attention mechanism to weight the input feature maps so that the model can focus on important contextual information around the target and improve the model's ability to handle complex scenes. The experimental results show that the improved YOLOv7 model achieves an average detection accuracy mAP value of 80.4%, which is 2.8% higher than the original algorithm, and the algorithm is better than the original YOLOv7 algorithm in terms of detection accuracy and speed, which is more suitable for the detection of underwater targets.

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

Citation Download Citation

Hongwei Zhuang and Weisheng Liu "Application of optimized deformable convolution in underwater biological detection algorithm", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132102V (11 July 2024); https://doi.org/10.1117/12.3034892

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KEYWORDS

Target detection

Convolution

Detection and tracking algorithms

Deformation

Performance modeling

Object detection

Submerged target modeling

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