Research on Monitoring Teaching Activities Based on Image Recognition in Educational Management Informatization Construction of Colleges and Universities

[1] Pham, T. N., Nguyen, N. P., Dinh, N. M. Q., & Le, T. (2022, September). Developing a Student Monitoring System for Online Classrooms Based on Face Recognition Approaches. In International Conference on Computational Collective Intelligence (pp. 555-567). Cham: Springer International Publishing. Search in Google Scholar

[2] Sukumaran, A., & Manoharan, A. (2023). A survey on automatic engagement recognition methods: online and traditional classroom. Indonesian Journal of Electrical Engineering and Computer Science, 30(2), 1178-1191. Search in Google Scholar

[3] Tang, J., Zhang, P., & Zhang, J. (2023). Design and implementation of intelligent evaluation system based on pattern recognition for microteaching skills training. Int. J. Innov. Comput. Info. Control, 1(19), 153-162. Search in Google Scholar

[4] Nguyen, P. D., Nguyen, H. Q., Nguyen, T. B., Le, T. L., Tran, T. H., Vu, H., & Huu, Q. N. (2022, October). A new dataset and systematic evaluation of deep learning models for student activity recognition from classroom videos. In 2022 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) (pp. 1-6). IEEE. Search in Google Scholar

[5] Lin, F. C., Ngo, H. H., Dow, C. R., Lam, K. H., & Le, H. L. (2021). Student behavior recognition system for the classroom environment based on skeleton pose estimation and person detection. Sensors, 21(16), 5314. Search in Google Scholar

[6] Hsu, T. C., Chang, C., & Jen, T. H. (2023). Artificial Intelligence image recognition using self-regulation learning strategies: effects on vocabulary acquisition, learning anxiety, and learning behaviours of English language learners. Interactive Learning Environments, 1-19. Search in Google Scholar

[7] Akila, D., Garg, H., Pal, S., & Jeyalaksshmi, S. (2024). Research on recognition of students attention in offline classroom-based on deep learning. Education and Information Technologies, 29(6), 6865-6893. Search in Google Scholar

[8] Mou, A., Milanova, M., & Baillie, M. (2022, August). Active Learning Monitoring in Classroom Using Deep Learning Frameworks. In International Conference on Pattern Recognition (pp. 384-393). Cham: Springer Nature Switzerland. Search in Google Scholar

[9] Harikrishnan, J., Sudarsan, A., Sadashiv, A., & Ajai, R. A. (2019, March). Vision-face recognition attendance monitoring system for surveillance using deep learning technology and computer vision. In 2019 international conference on vision towards emerging trends in communication and networking (ViTECoN) (pp. 1-5). IEEE. Search in Google Scholar

[10] Zhang, H., & Li, Y. (2024). Student Classroom Teaching Behavior Recognition Based on DSCNN Model in Intelligent Campus Education. Informatica, 48(9). Search in Google Scholar

[11] Xie, Y., Zhang, S., & Liu, Y. (2021). Abnormal Behavior Recognition in Classroom Pose Estimation of College Students Based on Spatiotemporal Representation Learning. Traitement du Signal, 38(1). Search in Google Scholar

[12] Sharma, V., Gupta, M., Kumar, A., & Mishra, D. (2024). STAR-3D: A Holistic Approach for Human Activity Recognition in the Classroom Environment. Information, 15(4), 179. Search in Google Scholar

[13] Shenoy, A., & Thillaiarasu, N. (2022, March). A survey on different computer vision based human activity recognition for surveillance applications. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 1372-1376). IEEE. Search in Google Scholar

[14] Mukherjee, P., Mondal, A., Dey, S., Layek, A., Neogi, S., Gope, M., & Gupta, S. (2021, December). Monitoring, recognition and attendance automation in online class: combination of image processing, cryptography in IoT security. In International Conference on Network Security and Blockchain Technology (pp. 18-27). Singapore: Springer Nature Singapore. Search in Google Scholar

[15] Wu, S. (2021). Simulation of classroom student behavior recognition based on PSO-kNN algorithm and emotional image processing. Journal of Intelligent & Fuzzy Systems, 40(4), 7273-7283. Search in Google Scholar

[16] Rashmi, M., Ashwin, T. S., & Guddeti, R. M. R. (2021). Surveillance video analysis for student action recognition and localization inside computer laboratories of a smart campus. Multimedia Tools and Applications, 80(2), 2907-2929. Search in Google Scholar

[17] Dimitriadou, E., & Lanitis, A. (2023). Student Action Recognition for Improving Teacher Feedback During Tele-Education. IEEE Transactions on Learning Technologies. Search in Google Scholar

[18] Pabba, C., & Kumar, P. (2022). An intelligent system for monitoring students’ engagement in large classroom teaching through facial expression recognition. Expert Systems, 39(1), e12839. Search in Google Scholar

[19] Dimitriadou, E., & Lanitis, A. (2023). Evaluating the potential of using automated action recognition for monitoring student activity in tele-education. In INTED2023 Proceedings (pp. 3605-3609). IATED. Search in Google Scholar

[20] Zhuang, J., & Huang, W. (2021, October). Design and implementation of intelligent teaching attendance system based on image recognition. In Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering (pp. 516-520). Search in Google Scholar

[21] Li, S., & Chai, H. (2021). Recognition of Teaching Features and Behaviors in Online Open Courses Based on Image Processing. Traitement du Signal, 38(1). Search in Google Scholar

[22] Alruwais, N., & Zakariah, M. (2024). Student Recognition and Activity Monitoring in E-Classes Using Deep Learning in Higher Education. IEEE Access. Search in Google Scholar

[23] SUN Rui,YANG Zi,ZHANG Lei & YU Yiheng. (2022). Orthogonal Deep Feature Decomposition Network for Cross-Resolution Person Re-Identification. IEICE Transactions on Information and Systems(11), 1994-1997. Search in Google Scholar

[24] Song Bin,Zhu Hong & Bi Yuandong. (2024). A conditioned feature reconstruction network for few-shot classification. Applied Intelligence(8),6592-6605. Search in Google Scholar

[25] Yuhua Li,Mengyue Zhang,Chunyu Zhang,Hui Liang,Pu Li & Wangwei Zhang. (2024). YOLO-CCS: Vehicle detection algorithm based on coordinate attention mechanism. Digital Signal Processing104632-104632. Search in Google Scholar

[26] Lifeng Gao,Tongkai Xu,Meiyu Liu,Jialin Jin,Li Peng,Xiaoting Zhao... & Sheng Liang. (2024). Ai-aided diagnosis of oral X-ray images of periapical films based on deep learning. Displays102649-. Search in Google Scholar