我所侯涛刚老师课题组完成的论文《Edge-to-client real-time road damage detection system based on Yolov5》于2022-01在《China Automation Congress (CAC)》正式发表。论文摘要如下：
Abstract: Road Damage may result in a reduction in the efficiency of traffic, and even endanger the safety of human and property. To realize automatic and timely detection of road damage, in this article, we design an edge-to-client road damage detection system based on the YOLO object detection algorithm, which includes roadside information collection platform, edge computing equipment, cloud transfer system, and client. We compared the effects of YOLOv5, YOLOv4, and YOLOv4-tiny on the RDD2020 data set and implemented model deployment and model optimization based on the NVIDIA Jetson NX platform. Experimental results show that the system can realize real-time display of road damage detection.
引用信息：MingJue Li, Hao Wang, Yuhang Peng, Xuan Pei, Tianmiao Wang, Taogang Hou. Edge-to-client real-time road damage detection system based on Yolov5. China Automation Congress (CAC), 2022-01. DOI: 10.1109/cac53003.2021.9727536