Substation bird detection based on feature selection and attention mechanism

Yunhao Shu; Guanying Zhang; Jiangcan Jia; Wenming Zhu; Jianxun Ma

doi:10.1117/12.3049300

12 November 2024 Substation bird detection based on feature selection and attention mechanism

Yunhao Shu, Guanying Zhang, Jiangcan Jia, Wenming Zhu, Jianxun Ma

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Proceedings Volume 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) ; 133952V (2024) https://doi.org/10.1117/12.3049300
Event: International Conference on Optics, Electronics, and Communication Engineering, 2024, Wuhan, China

Abstract

To reduce the loss of labor force and material resources caused by bird activities at the substations and address the problems of high detection difficulty for small bird targets within complex backgrounds, a bird target detection method based on feature selection and attention mechanism is proposed. Specifically, the feature selection module (FSM) is initially used to extract key information from multi-level features. In order to enable the model concentrating on crucial channels and spatial positions related to the small target, coordinate attention is further embedded in the improved bidirectional feature pyramid network. Finally, a feature fusion module (FFM) is designed to utilize advanced semantic information, enhancing low-level detail features and improving the ability to capture subtle features. Finally, ablation and comparative experiments are conducted on a self-made bird target dataset in the background of substations. Experimental results demonstrate that this method has good performance in bird target detection scenarios in substations.

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

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Yunhao Shu, Guanying Zhang, Jiangcan Jia, Wenming Zhu, and Jianxun Ma "Substation bird detection based on feature selection and attention mechanism", Proc. SPIE 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) , 133952V (12 November 2024); https://doi.org/10.1117/12.3049300

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