Research on weakly supervised target localization in sonar imagery based on GradCAM

Guangze Wei; Jianlei Zhang; Chen Wang; Guangming Xie; Xiao Zhang; Minglei Xiong

doi:10.1117/12.3037808

12 September 2024 Research on weakly supervised target localization in sonar imagery based on GradCAM

Guangze Wei, Jianlei Zhang, Chen Wang, Guangming Xie, Xiao Zhang, Minglei Xiong

Author Affiliations +

Proceedings Volume 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); 132560B (2024) https://doi.org/10.1117/12.3037808
Event: Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 2024, Anshan, China

Abstract

In the unique marine environment, sonar, as a crucial tool for navigation and ranging using sound waves, plays a key role in the recognition and localization of targets in sonar imagery, which is critical to the performance of underwater equipment. In practical applications, fully supervised object detection methods are commonly used to accurately determine the categories and locations of targets in sonar images. However, these methods require laborious individual annotation of target positions and categories. Addressing this challenge, this paper proposes a weakly supervised target localization method for sonar imagery based on Grad-CAM technology. Initially, the method employs the Balanced Ensemble Transfer Learning (BETL) algorithm for target classification in sonar images, utilizing deep transfer learning. Subsequently, the GradCAM technique is applied to the task of sonar image target classification, using the generated heat maps for target localization. This aims to enhance the accuracy and efficiency of sonar image recognition and localization while reducing the burden of annotation work.

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

Citation Download Citation

Guangze Wei, Jianlei Zhang, Chen Wang, Guangming Xie, Xiao Zhang, and Minglei Xiong "Research on weakly supervised target localization in sonar imagery based on GradCAM", Proc. SPIE 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 132560B (12 September 2024); https://doi.org/10.1117/12.3037808

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