Author(s)

Jing Zhao ¹

Affiliation(s)

¹ School of Art and Information Engineering, Dalian University of Technology, Dalian, 116600, China

Corresponding Author

Jing Zhao

ABSTRACT

This study, based on deep learning technology, aims to explore the research and practice of applying Photoshop in higher education. Combining the needs of university teaching, we have successfully achieved a more efficient and intelligent application of Photoshop, effectively enhancing the quality and efficiency of image processing. The paper provides a detailed introduction to the basic principles of deep learning in the field of image processing and elaborates on its specific applications and practical experiences in Photoshop usage in higher education. Through experimental verification, we conclude that the deep learning technology proposed in this study has good feasibility and practicality in Photoshop teaching in higher education.

KEYWORDS

Higher Education, Photoshop, Image Processing, Deep Learning, Intelligentization

CITE THIS PAPER

Jing Zhao, Research and practice of Photoshop application technology in high universities based on deep learning. Journal of Image Processing Theory and Applications (2024) Vol. 7: 19-25. DOI: http://dx.doi.org/10.23977/jipta.2024.070103.

REFERENCES

[1] Cheng Jie. hotoshop Applied study of course case development practice [J]. Technology wind. 2022(02):17-19.
[2] Tao Yujuan. Exploration of Teaching Mode for Computer Aided Design Courses—— Take the Photoshop course as an example [J]. Research on fine Arts education. 2023(11):158-160.
[3] Li Xiangling. Exploration and thinking on the teaching reform of Photoshop curriculum in the middle and micro courses in schools [J]. The Internet Weekly. 2023(13):93-95.
[4] Chen Lei. Design, development and application of micro course of Photoshop Image Processing in universities [J]. Computer knowledge and technology. 2020,16(29):119-120.
[5] Jiang Nannan. Photoshop Application of graphic information processing technology in intelligent teaching courseware in universities [J]. Guangdong printing. 2022(06):53-55.
[6] Wang Qian. Exploration on the application of educational big data mining based on deep learning technology [J]. Digital communication world. 2023(11):112-114.

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