Lei Hu1,*, Yuanwen Lu1, Si Wang2, Wenbin Wang3, Yongmei Zhang4
CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2735-2749, 2023, DOI:10.32604/cmc.2023.042974
Abstract The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle (UAV) due to the complex background of distribution lines, variable morphology of equipment, and large differences in equipment sizes. Therefore, aiming at the difficult detection of power equipment in UAV inspection images, we propose a multi-equipment detection method for inspection of distribution lines based on the YOLOx-s. Based on the YOLOx-s network, we make the following improvements: 1) The Receptive Field Block (RFB) module is added after the shallow feature layer of the backbone network to… More >
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