基于机器视觉的智能物流配送实验教学系统设计

Xin Wang, Jintao Chen, Cong Li, Huiying Ma, Zhi Qi, Lihong Song
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引用次数: 0

摘要

物流配送被广泛应用于许多领域。本文设计了一种基于STM32F103单片机和机器视觉传感器的智能物流配送实验教学系统。采用基于改进LeNet-5的卷积神经网络模型对目的地号码信息进行识别。可以同时识别和跟踪导航信息。所有信息均可通过串口发送到上位机进行处理。实验结果表明,该智能物流配送系统能够快速完成目标号码识别,达到较高的准确率。该系统具有成本低、难度适中、性能稳定等优点。具有一定的实验教学和实际应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Intelligent Logistics Delivery Experiment Teaching System based on Machine Vision
Logistics delivery is widely used in many fields. This paper designs an intelligent logistics delivery experimental teaching system based on STM32F103 microcomputer and machine vision sensor. The convolutional neural network model based on improved LeNet-5 is applied to identify information of the destination number. The navigation information can be identified and traced at the same time. All information can be sent to the host computer through the serial port for processing. The experimental results show that the intelligent logistics delivery system can quickly complete the target number recognition and achieve high accuracy. The system has the advantages of low cost, moderate difficulty and stable performance. It has a certain value of experimental teaching and practical application.
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