Exploration of the Teaching Reform of Machine Vision Courses Based on Local Industrial Requirements

随着智能制造和人工智能技术的快速发展，机器视觉作为核心技术之一，对高素质应用型人才的需求日益迫切。然而，传统教学模式普遍存在教学内容滞后、实践环节薄弱、与产业需求脱节等问题。本文以本地产业需求为导向，从课程体系重构、校企协同育人、动态案例开发、多维度评价机制等方面开展教学改革，探索“产业需求牵引、项目任务驱动、能力分层培养”的教学模式。通过整合区域产业资源、设计梯度化实践项目、引入真实生产案例，有效提升了学生的工程实践能力和职业竞争力，为地方高校培养适应区域经济发展的机器视觉人才提供了可借鉴路径。With the rapid development of intelligent manufacturing and artificial intelligence technologies, machine vision, as one of the core technologies, has an increasing urgent demand for high-quality applied talents. However, traditional teaching models generally suffer from problems such as lagging teaching content, weak practical links, and a disconnection from industrial requirements. Guided by local industrial requirements, this paper conducts teaching reforms in aspects such as curriculum system reconstruction, school-enterprise collaborative education, dynamic case development, and multi-dimensional evaluation mechanisms, and explores a teaching model of “industrial requirement-driven, project task-driven, and ability-leveled training”. By integrating regional industrial resources, designing gradient practical projects, and introducing real production cases, it effectively improves students’ engineering practice abilities and professional competitiveness, providing a reference path for local universities to cultivate machine vision talents who can adapt to regional economic development.