Exploration of AI-empowered Machine Vision Algorithms and Applications Course

Abstract

With the rapid popularization of artificial intelligence technology, traditional machine vision courses can no longer keep pace with the industry’s demand for interdisciplinary talents proficient in “AI + Vision” in terms of teaching content, practical training and assessment methods. To address the problems existing in the curriculum, such as disconnection between theory and practice, outdated knowledge content and insufficient engineering training, this paper proposes an AI-enabled reform approach for machine vision courses. By constructing an “AI + Education” smart teaching platform, optimizing teaching methods and improving assessment mechanisms, we have built a three-dimensional practical platform featuring project-driven, virtual-real integrated and industry-education coordinated development, as well as a comprehensive evaluation system that is process-based, diversified and capability-oriented. Teaching practice has proved that this reform has effectively enhanced students’ learning initiative, significantly improved their abilities in solving complex engineering problems, innovative thinking and teamwork, and provided a feasible solution for cultivating high-quality engineering and technical talents to meet the development needs of the intelligent industry.