A fast tree obstacle small target location algorithm for electric power operation scene based on self-supervised vision transformer

Conventional fast location algorithm for small target in power operation scene tree obstacle mainly uses ECKF (Embedded Cube Kalman Filter) embedded volume Kalman filter to create a random location function, which is vulnerable to changes in random parameters, resulting in poor location performance. Therefore, a fast location algorithm for small target in power operation scene tree obstacle based on self supervised visual transformer is proposed. That is to say, the self supervised vision transformer is used to design a fast positioning framework for small targets in the power operation scene tree obstacle, thus generating a fast positioning optimization algorithm for small targets in the power operation scene tree obstacle. The experimental results show that the designed fast location algorithm for small target with tree obstacle has high location accuracy, low miss detection rate and false detection rate, which proves that the designed fast location method for small target with tree obstacle in power operation scenarios has good location performance, effectiveness and certain application value, and has made certain contributions to reducing the risk of power operation.