Lightweight detection network for grid worker recognition
Aiming at the problems of low monitoring accuracy and coverage caused by the diversity of power grid construction environment and the existence of monitoring blind areas in traditional methods,a lightweight detection network dedicated to the identification of power grid workers was proposed to monitor the work behavior of power grid workers through the high-altitude and ground three-dimensional patrol mode.A lightweight target detection network was used to detect the power grid workers in the surveillance video,and judge whether they wore helmets or not,and then the personal recognition network was used to identify the worker not wearing helmets.The simulation results show that the as-proposed method can realize the three-dimensional inspection of the work behavior of power grid workers.Compared with the traditional method,the as-proposed method has lesser computation and can achieve a recognition accuracy of 63.4%.
国家科技期刊平台
NSTL
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