A transformer-YOLO-based method for construction machinery monitoring in transmission channels

This article proposes a Transformer-YOLO model for identifying hidden dangers in construction machinery to address the issues of complex transmission channel environments, diverse forms of construction machinery, and significant changes in target scales. Firstly, A transformer-based prediction head is adopted in YOLO v5. Then, the CNN module is replaced by DCN-V2. Finally, this paper optimized the loss function of the model to enhance its ability to detect small targets. This article uses online monitoring images to construct a dataset and validates the model. The results show that the method proposed in this article can effectively identify and alert construction machinery targets near the transmission channel.