Research on YOLOv5 Vehicle Object Detection Algorithm Based on Attention Mechanism

In intelligent transportation systems, the study of vehicle object detection is of great importance. In order to improve the performance of object detection, an improved method based on YOLOv5 is used for vehicle object detection, and a YOLOv5x vehicle multi-object detection optimization algorithm based on attention mechanism is proposed by adding attention mechanism modules to different modules of the network for network optimization, and the algorithm is validated on the traffic dataset constructed in the paper to show the feasibility of the improved strategy. According to the experimental results, it can be seen that the improved detection algorithm improves the mAP by more than 10% compared with the original detection algorithm, which is better than the original detection algorithm.