摘要
Abstract
In the intelligent logistics system for the furnace front at Masteel Rail Transit Mate-rials Technology Co.,Ltd.,the quantity of round billets on the conveyor line pallets was originally provided solely by the logistics system itself,lacking an effective post-verification mechanism.To ad-dress this issue,a visual inspection system based on YOLOv8(You Only Look Once,v denotes ver-sion)was proposed.This system is designed to identify and detect the placement positions and quan-tities of materials on the pallets.The recognition results are then sent to the intelligent logistics sys-tem for comparison with the original data stored within the system,thereby ensuring the accuracy of material information.This visual recognition system effectively serves as a post-verification step.Field test results demonstrate that by optimizing the YOLOv8 network structure,the system's detec-tion and recognition accuracy exceeds 99.4%,meeting the requirements of practical applications.关键词
智慧物流/YOLOv8/实时目标检测/圆坯计数/深度学习Key words
intelligent logistics/YOLOv8/real-time object detection/round billet counting/deep learning分类
信息技术与安全科学
