With the rapid development of power grid construction, transmission lines, as the lifeline of energy transmission, their stability and safety are directly related to national energy security and people's well-being. In the daily maintenance of transmission lines, anti-corrosion work is a crucial task. However, the traditional anti-corrosion methods mostly rely on manual operation, which is not only inefficient, but also has huge potential safety risks, and it is difficult to ensure the uniformity of spraying. To solve these problems, unmanned aerial vehicle (UAV) technology, with its high efficiency, high flexibility and safety, has opened up a new path for the precise application of anti-corrosion coatings on transmission lines. This study focuses on the UAV-assisted precise application technology of anti-corrosion coating on transmission lines, and introduces the deep learning (DL)-driven transmission line detection algorithm, which successfully achieves the accurate identification and location of transmission line sections. This algorithm can deeply analyze the image data of transmission lines, extract key features, and then accurately identify the cross section of transmission lines. The experimental data show that the algorithm has achieved remarkable results in the detection of transmission lines, laying a solid foundation for the accurate application of anti-corrosion coatings in the future.