In today's era of highly developed spiritual civilization, art education has been paid more and more attention. In order to popularize art knowledge and cultivate college students' aesthetic literacy and other tasks, major colleges and universities have set up art appreciation courses. The art appreciation course is set up for college students, the purpose is to develop the aesthetic quality of college students, so that they can acquire critical thinking and enrich aesthetic experience. However, at present, the art appreciation class still has defects in both theoretical research and practice, which does not conform to the important concept of cultivating high-quality talents as the core advocated by higher art education. For a long time, teachers, teaching administrators and researchers lacked due attention and discussion on the teaching of art education. Therefore, based on the convolutional neural network, this paper integrated the emotion recognition algorithm into the art education teaching, and sorted out the main points of art education's aesthetic intervention for college students. The test results showed that under the art teaching based on emotion recognition algorithm, about 8.04% of students' aesthetic ability has been effectively improved. The cultivation of college students' aesthetic ability would help to promote the all-round development of college students and had a positive effect on promoting quality education.

Enze Li. Intervention of Art Education on College Students' Aesthetic Mood Based on Emotion Recognition Algorithm. Frontiers in Art Research (2024) Vol. 6, Issue 9: 81-90. https://doi.org/10.25236/FAR.2024.060914.

[1] Liu R. Innovation Mode of Art Education in Colleges and Universities Based on Big Data[J]. Journal of Physics Conference Series, 2021, 1852(3):27-32.

[2] Raymond, Elman, Charity. Understanding the Value of Art Education: A Video Discussion with Alberto Carvalho, Superintendent of Miami-Dade County Public Schools[J]. Inspicio, 2017, 3(2):8-9.

[3] Jeong-Ae, Park. Postmodern Art Education: Understanding Cultures through Art[J]. Journal of Research in Art Education, 2017, 18(1):1-24.

[4] Martynyshyn Y, Feicher O. Subsystems for functional support of organizational and economic mechanism of management of art higher education institutions[J]. Problems of Innovation and Investment Development, 2021, 25(3):149-165.

[5] Dede B. The contributions of academies, modern educational institutions, to education of art in Europe[J]. Ulakbilge Dergisi, 2017, 5(3):1125-1136.

[6] Lee M J. An Aesthetic Approach of Art Education by Defining the Values and Concept of Art[J]. Journal of Research in Art Education, 2019, 20(3):43-58.

[7] Lavrinets A. Modern trends of art post-graduate pedagogical education[J]. ScienceRise Pedagogical Education, 2018, 24(4):47-50.

[8] Yu G. Emotion Monitoring for Preschool Children Based on Face Recognition and Emotion Recognition Algorithms [J]. Complexity, 2021, 2021(5):1-12.

[9] Tang C, Li Y, Chen B. Comparison of cross-subject EEG emotion recognition algorithms in the BCI Controlled Robot Contest in World Robot Contest 2021 [J]. Neuroscience (English), 2022, 8(2):11-12.

[10] Nakisa, Bahareh, Rastgoo. Evolutionary computation algorithms for feature selection of EEG-based emotion recognition using mobile sensors [J]. Expert Systems with Application, 2018, 93(6):143-155.

[11] Gabriels K. Response to "uncertainty in emotion recognition"[J]. Journal of Information Communication and Ethics in Society, 2019, 17(3):295-298.

[12] Kyeong, Tae, Kim. Weighted Soft Voting Classification for Emotion Recognition from Facial Expressions on Image Sequences[J]. Journal of Korea Multimedia Society, 2017, 20(8):1175-1186.

[13] Gunawan T S, Alghifari M F, Morshidi M A. A review on emotion recognition algorithms using speech analysis[J]. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2018, 6(1):12-20.

[14] Nakisa B, Rastgoo M N, Tjondronegoro D. Evolutionary computation algorithms for feature selection of EEG-based emotion recognition using mobile sensors[J]. Expert Systems with Applications, 2018, 93(6):143-155.

[15] Latha C P, Priya M. A Review on Deep Learning Algorithms for Speech and Facial Emotion Recognition [J]. APTIKOM Journal on Computer Science and Information Technologies, 2020, 1(3):92-108.

[16] Chidothe M, Cohn E. Effects of adult health interventions at scale on children schooling: Evidence from antiretroviral therapy in Zambia[J]. Economics of Education Review, 2019, 72(7):107-120.

[17] Akyurek T, Akkaya T. Importance Of Art Education Artistic Anatomy: Action Research[J]. Ulakbilge Dergisi, 2019, 7(13):43-45.

[18] Adlin D. Aesthetic Concept - Choreography of Piso Surit Dance in Karo Community[J]. Budapest International Research and Critics in Linguistics and Education (BirLE) Journal, 2020, 3(1):172-182.

[19] Zhou Y, Chen H, Li Y. 3D multi-view tumor detection in automated whole breast ultrasound using deep convolutional neural network[J]. Expert Systems with Applications, 2021, 168(12):14-41.

[20] Bhowmick D, Sengupta P. The topological magnon bands in the Flux state in Sashtry-Sutherland lattice [J]. Physical review. B, Condensed matter, 2020, 101(1):24-43.