摘要
随着人工智能领域的快速发展,机器视觉技术从以前依赖于传统图像处理方法发展到结合深度学习,并已得到广泛应用。针对上述趋势,设计了一个可降低学习门槛的基于深度学习的机器视觉实验系统。该系统使用Robomaster EP机器人、AI端侧模块和AI训练平台,实验内容涵盖深度学习在机器视觉领域应用时的全部流程,包括数据采集、数据标注、模型训练部署和实践,无需复杂的软件环境配置,界面直观,易于实践,对个人编程经验要求较低,可扩展至非计算机和人工智能专业学生。应用实践结果表明,所设计的实验系统操作简易,兼具实用性和可扩展性,有助于学生直观地理解深度学习技术在机器视觉领域的具体应用过程,激发其对后续深入学习的兴趣。
Machine vision is a key technology in modern industrial manufacturing which previously relied on traditional image processing method.With the rapid development in artificial intelligence,machine vision technology develops from traditional image processing method to integration with deep learning,and receives a wide application.In response to this trend,an experiment system based on deep learning for machine vision is designed to lower the learning barrier.The experiment system utilizes the RoboMaster EP robot,AI edge module,and AI training platform,covers the entire process of applying deep learning in the field of machine vision,including data collection,data annotation,model training,deployment,and practice,without the need for complex software environment configuration.The experiment system has simple interface and easy to learn,requires little programming experience,and is also suitable for those not majoring in computer science and artificial intelligence.The application results indicate that the system is easy to learn,practical,and scalable.It can help students intuitively understand the specific application process of deep learning technology in the field of machine vision and has stimulated their interest in further in-depth learning.
作者
邓睿
胡继华
范红伟
李明洋
黄建亮
Deng Rui;Hu Jihua;Fan Hongwei;Li Mingyang;Huang Jianliang(School of Aeronauties and Astronauties,Sun Yat-sen University,Shenzhen,Guangdong 518000,China)
出处
《机电工程技术》
2024年第5期183-186,共4页
Mechanical & Electrical Engineering Technology
基金
教育部产学合作协同育人项目(231103084222521)
中山大学2024年教学质量工程项目(以综合性工程素质培养为核心的工程训练项目制教学改革探究)。
关键词
深度学习
人工智能
机器视觉
实验
deep learning
artificial intelligence
machine vision
experiment
