基于LECA-YOLOv5的物流仓储异常行为识别算法

Identification Algorithm of Abnormal Behavior in Logistics Warehousing Based on LECA-YOLOv5

随着人工智能技术的发展,各行各业都开始尝试利用计算机实现高效的工作模式,同样电子商务的运营也离不开互联网的支撑。电子商务的基础是物流。高效的工作模式、智能化的信息是物流快速发展的基础。本文将双目立体视觉引入到物流仓库的监测中,通过双目相机监测货物和工作人员的位置信息,并利用改进的目标检测算法LECA-YOLOv5检测工作人员异常行为,以提高物流仓库的工作效率和安全水平。

With the development of artificial intelligence technology,all walks of life use computers to achieve efficient working modes,and the operation of e-commerce can not be separated from the support of the Internet.As the basis of e-commerce,logistics,efficient working modes and intelligent information are the basis for the rapid development of logistics.In this paper,binocular stereo vision is introduced into the monitoring of logistics warehouse,and the location information of goods and staff is monitored through binocular cameras.The improved target detection algorithm LECA-YOLOv5 is used to detect abnormal behavior of staff,so as to improve the working efficiency and security level of logistics warehouse.