Road Aerial Object Detection Based on Improved YOLOv5

Abstract In this paper, the target detection technology based on deep learning is applied to process of object in highway aerial photography. By detecting road objects such as vehicles or crosswalk, it lays foundation for digitalization and informationization roads. Firstly, unmanned vehicle used collect images. Then YOLOv5 network, aiming at problem small target, attention mechanism introduced weigh different channels feature graph, SoftPool SPP module improve pooling operation retain more detailed information. The experimental results show that improved network can identify locate roads accurately effectively.