In order to use UAV aerial images to detect transmission lines to ensure the stable operation of power system,a transmission line detection method based on weak supervised learning and non paired image transformation is proposed.The weak supervised learning framework is used to generate the location mask of the transmission line.By introducing a new parallel dilated attention(PDA)module to integrate information from different receptive fields,the importance of the chan-nel is recalibrated and the detection accuracy is improved.The algorithm based on association rule learning is used to gener-ate pseudo wire data set,and the refining network is constructed by using the attention location mask(ALM)in PDA and the non paired image conversion technology between pseudo wire data,so as to enhance the linear characteristics of transmis-sion lines and realize direct detection only by image level labels.The experimental results show that the proposed detection method is 2.74％better than the current most advanced recursive noise-based learning update(RNLU)method in terms of F1 score,and the ablation experiments verify that each step of the refining network is effective.
关键词
弱监督学习/图像间转化/输电线路/无人机/注意力机制
Key words
weak supervised learning/image to image conversion/transmission line/UAV/attention mechanism
维普
万方数据