YOLOv7 Vehicle Target Detection Algorithm Based on Attention Mechanism

While pedestrian target detection methods have advanced considerably, vehicle target detection still holds significant potential in the field of intelligent identification. However, this task faces challenges due to factors like lighting, environmental conditions, and occlusion, which could affect detection accuracy. This study focuses on vehicle target detection, aiming to address the difficulties of detecting and avoiding missed detections of vehicles in complex backgrounds. By utilizing the YOLOv7 algorithm, we constructed a dataset that includes complex backgrounds and small-scale vehicle images, integrated the Coordinate Attention mechanism, adding CA attention mechanism, designing the algorithm model YOLOv7-veh, training the model, and performing target recognition on vehicles respectively, the superiority of YOLOv7-veh algorithm in complex background and small-scale vehicle target detection is proved through comparative tests.