Lightweight dual scale angle transformation network for accurate detection of power components

Huiting Liu; Huimin Wang; Yaqian Xu; Rui Du

doi:10.1117/12.2680920

8 June 2023 Lightweight dual scale angle transformation network for accurate detection of power components

Huiting Liu, Huimin Wang, Yaqian Xu, Rui Du

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 1270728 (2023) https://doi.org/10.1117/12.2680920
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

The detection technology of infrared thermal imaging is becoming more and more mature. With the wide application of deep learning, the accurate detection method of infrared image power components based on object detection occupies the mainstream of the market. The existing accurate detection methods of power components mainly have problems such as difficulty in taking into account the speed and accuracy, and low recall rate of rotating targets. This paper proposes a Lightweight Dual Scale Angle Transform Network (LDS-ATN). Based on the lightweight backbone network, an angle transform module is introduced to enhance the angle correction. Finally, this paper achieves an average accuracy of 89.89% and a detection speed of 127.27 FPS on the task of accurate detection of electrical components. It proves the practicability and generalizability of this network in power detection.

Citation Download Citation

Huiting Liu, Huimin Wang, Yaqian Xu, and Rui Du "Lightweight dual scale angle transformation network for accurate detection of power components", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 1270728 (8 June 2023); https://doi.org/10.1117/12.2680920

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