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The path and exploration of building the first-class course of machine vision

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DOI: 10.23977/jaip.2024.070121 | Downloads: 8 | Views: 162

Author(s)

Zhe Liu 1, Jie Jiang 1, Yahong Ma 1

Affiliation(s)

1 School of Electronic Information, Xijing University, Xi'an, 710123, China

Corresponding Author

Zhe Liu

ABSTRACT

According to the development plan of "Made in China 2025" released by the State Council, intelligent manufacturing, as a new strategic pillar industry in China, is the main direction for advancing the strategy of building a strong manufacturing country. Accelerating the cultivation of professional technical talents needed for the development of the intelligent manufacturing industry is an urgent and significant task facing various universities in China. The course of machine vision, hailed as the "eyes" of intelligent manufacturing, is crucial for improving manufacturing efficiency and the level of intelligent automation. This paper, starting from the construction of the "Machine Vision" course at Xijing University, explores a path of course development focusing on the significant demands of the China intelligent manufacturing industry. It is based on the principles of "industry-education integration, study-education integration, science-education integration, and ideology-education integration." Through the reconstruction of course content, practical aspects, course projects, and ideological and political education, the organic integration of the course system with the demands of the intelligent manufacturing industry is achieved. This approach has yielded significant results and can be effectively extended and promoted to other engineering courses, facilitating the transformation and upgrading of traditional engineering courses.

KEYWORDS

Intelligent Manufacturing, Machine Vision, Course Development, Artificial Intelligence, First-Class Course

CITE THIS PAPER

Zhe Liu, Jie Jiang, Yahong Ma, The path and exploration of building the first-class course of machine vision. Journal of Artificial Intelligence Practice (2024) Vol. 7: 139-145. DOI: http://dx.doi.org/10.23977/jaip.2024.070121.

REFERENCES

[1] Gao Qingsong, Li Ting. Research Progress and Review on "Made in China 2025." Industrial Technology and Economy, 2018, 300(10): 59-66. 
[2] State Council. Notice of the State Council on Printing and Distributing the "Made in China 2025" (Guofa [2015] No. 28). Beijing: State Council, 2015. 
[3] Ministry of Education. Implementation Opinions of the Ministry of Education on the Construction of First-Class Undergraduate Courses (Jiaogao [2019] No. 8). Beijing: Ministry of Education, 2019. 
[4] Yang Ruofan, Liu Jun, Li Xiaojun. Reflections and Practices on Collaboratively Cultivating Innovative Talents in Intelligent Manufacturing. Research on Higher Engineering Education, 2018(5): 30-34. 
[5] Wang Shutin, Xie Yuanlong, Yin Zhouping, Ding Han. Construction and Practice of Innovative Talent Cultivation System for Intelligent Manufacturing in the New Engineering Discipline. Research on Higher Engineering Education, 2022(5): 12-18. 
[6] Cao Peijie. The Three Realms of the Education Revolution of Artificial Intelligence. Educational Research, 2022, 481(2): 143-150.

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