Open Access

Research on the Influence of College Ideological and Political Education on Students’ Mental Health Based on Deep Learning

 and    | Apr 10, 2024

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Leon, R., Wingrove, S., & Kay, A.C. (2020). Scientific skepticism and inequality: political and ideological roots. Journal of Experimental Social Psychology, 91(7), 104045. Search in Google Scholar

Limerick, N. (2017). Kichwa or quichua? competing alphabets, political histories, and complicated reading in indigenous languages. Comparative Education Review, 62(1), 1. Search in Google Scholar

Zhang, A., & Liu, F. (2017). Research on the computer-based multi-dimensional ideological and political education of college students. Revista de la Facultad de Ingenieria, 32(8), 303-310. Search in Google Scholar

Wang, K. (2017). Research on multi-dimensional ideological and political education of college students based on computer platform. Revista de la Facultad de Ingenieria, 32(8), 447-454. Search in Google Scholar

Du, Y. (2017). The development of ideological and political education information platform based on web technology. CeCa, 42(4), 1530-1536. Search in Google Scholar

Wang, N. (2021). Ideological and political education recommendation system based on AHP and improved collaborative filtering algorithm. Scientific Programming, 2021(13), 2021. Search in Google Scholar

Song, B., & Qiu, R. (2020). The influence of digital virtual technology on contemporary college students’ ideological and political education. IEEE Access, 2020(99), 1-1. Search in Google Scholar

Su, R. (2017). Evaluation-model-based research on the combination of internet platforms with the ideological and political education in colleges and universities. Revista de la Facultad de Ingenieria, 32(13), 681-686. Search in Google Scholar

Quan, L., Jiang, W., Li, H., Li, H., Wang, Q., & Chen, L. (2022). Intelligent intra-row robotic weeding system combining deep learning technology with a targeted weeding mode. Biosystems Engineering, 2022(216), 216. Search in Google Scholar

Choi, H., Lim, S., Min, K., Ahn, K.H., Lee, K.M., & Dong, P.J. (2021). Non–human primate epidural ecog analysis using explainable deep learning technology. Journal of Neural Engineering, 18(6), 066022-. Search in Google Scholar

Li, J., Liu, Y., Yin, C., Ren, X., & Su, Y. (2020). Fast imaging of time-domain airborne em data using deep learning technology. Geophysics, 85(5), 1-38. Search in Google Scholar

Tsai, M.F., Lin, P.C., Huang, Z.H., & Lin, C.H. (2020). Multiple feature dependency detection for deep learning technology—smart pet surveillance system implementation. Electronics, 9(9), 1387. Search in Google Scholar

Huang, Z., Mendis, T., & Xu, S. (2019). Urban solar utilization potential mapping via deep learning technology: a case study of wuhan, china. Applied Energy, 250(1), 283-291. Search in Google Scholar

Yang, X., Zhou, Z., & Xiao, Y. (2021). Research on students’ adaptive learning system based on deep learning model. Scientific Programming, 2021(13), 2021. Search in Google Scholar

He, H., & Jiang, H. (2019). Deep learning based energy efficiency optimization for distributed cooperative spectrum sensing. IEEE Wireless Communications, 26(3), 32-39. Search in Google Scholar

Li, Y.K., Wu, X.J., & Kittler, J. (2019). L1-2d2pcanet: a deep learning network for face recognition. Journal of Electronic Imaging, 28(2), 1. Search in Google Scholar

Lan Huiying, Wu, Linyang, Han, Dong, & Du. (2019). Assembly language and assembler for deep learning accelerators. High Technology Letters, 25(04), 42-50. Search in Google Scholar

Plotz, T., & Guan, Y. (2018). Deep learning for human activity recognition in mobile computing. Computer, 51(5), 50-59. Search in Google Scholar

Jiang, Y.Q., Xiong, J.H., Li, H.Y., Yang, X.H., & Sun, J.F. (2020). Using smartphone and deep learning technology to help diagnose skin cancer. British Journal of Dermatology, 182(3), e95-e95. Search in Google Scholar

Kinoshita, S., Wakatsuki, M., Horinouchi, S., Tanabe, S., & Higashi, A. (2019). Fujitsu’s deep learning technology that enables smart city monitoring. Fujitsu Scientific & Technical Journal, 55(2), 30-37. Search in Google Scholar

eISSN:
2444-8656
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics