Improved underwater seafood target recognition network based on YOLOv7

Xu Su; Zhijia Zhang

doi:10.1117/12.3039054

13 September 2024 Improved underwater seafood target recognition network based on YOLOv7

Xu Su, Zhijia Zhang

Author Affiliations +

Proceedings Volume 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024); 1325416 (2024) https://doi.org/10.1117/12.3039054
Event: Fourth International Conference on Optics and Image Processing (ICOIP 2024), 2024, Chongqing, China

Abstract

In complex underwater environments, it is difficult for traditional methods to accurately obtain position information of dense, fuzzy, and small-sized organisms. Although the convolutional neural network algorithm is popular, it is limited by insufficient training samples and other limitations, and the accuracy and speed improvement are poor. For this reason, this paper designs a YOLOv7-CBF network model based on the YOLOv7 network. By introducing the CBIF module and FasterNet module, the model fuses local and global information, improves the feature extraction capability, and reduces redundant computation to effectively extract contextual semantic information. Meanwhile, a new enhanced loss function ECLOU is proposed to improve the localisation accuracy and model robustness. Experiments prove that the model performs well in underwater seafood detection with high accuracy and speed, which meets the practical needs. This result is of great significance for facilitating seafood fishing, reducing cost and improving detection efficiency.

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

Citation Download Citation

Xu Su and Zhijia Zhang "Improved underwater seafood target recognition network based on YOLOv7", Proc. SPIE 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024), 1325416 (13 September 2024); https://doi.org/10.1117/12.3039054

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KEYWORDS

Feature extraction

Target detection

Submerged target modeling

Semantics

Detection and tracking algorithms

Performance modeling

Data modeling

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