A novel sonar image target detection model based on fast large kernel attention network

Shuang Liu; Jingjing Jian; Jianxun Tang

doi:10.1117/12.3038747

23 August 2024 A novel sonar image target detection model based on fast large kernel attention network

Shuang Liu, Jingjing Jian, Jianxun Tang

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132501L (2024) https://doi.org/10.1117/12.3038747
Event: 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

As artificial intelligence technology continues to advance, the utilization of deep learning in sonar image target detection is growing. This trend has garnered significant interest in maritime defense infrastructure and marine economic development as a promising research avenue. Nevertheless, existing sonar image target detection methods face challenges due to the inherent characteristics of sonar images, such as low resolution, blurred edges, and significant speckle noise. These issues often result in large model parameters and slow inference speeds. To mitigate these challenges, this study introduces a novel approach: a sonar image target detection model utilizing a Fast Large Kernel Attention Network (FLKANet). The FLKANet enhances feature extraction capabilities, reduces model parameters, and improves inference speed. Moreover, employing Large Separable Kernel Attention (LSKA) instead of Small Patch Feature Fusion (SPFF) enables the model to prioritize the shape of sonar targets over texture, thereby enhancing detection accuracy and inference speed. Experimental results on the SCTD sonar image dataset demonstrate the superiority of the proposed model in terms of parameter count, computational complexity, inference speed, and detection accuracy. These findings offer valuable insights for deploying edge-side models in future applications.

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

Citation Download Citation

Shuang Liu, Jingjing Jian, and Jianxun Tang "A novel sonar image target detection model based on fast large kernel attention network", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132501L (23 August 2024); https://doi.org/10.1117/12.3038747

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KEYWORDS

Target detection

Convolution

Feature extraction

Object detection

Performance modeling

Submerged target modeling

Feature fusion

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