A Review of Deep Learning-Based Student Behavior Recognition in the Classroom
Author:
Affiliation:
1. Wuhan Donghu University, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3671151.3671284
Reference10 articles.
1. Wang Z Ji Y Xue K 2024. Multi-Scale Classroom Behavior Recognition Study Based on CA-YOLOv7[C]//2023 International Conference on Image Processing Computer Vision and Machine Learning (ICICML).0 [2024-03-30]. DOI:10.1109/ICICML60161.2023.10424952.
2. Adson D, Andressa F, Thiago G, Celso M, Elane P, Understanding the Correlation Between Teacher and Student Behavior in the Classroom and its Consequent Academic Performance [C]. 2019 IEEE Frontiers in Education Conference, 2019, 1-9.
3. Fang M Yuan L Lei L .Multi-scale Mobile Phone Playing Behavior Recognition Based on Temporal Enhancement and Interaction [J]. 2021.
4. SOOMRO K, ZAMIR A R. Action Recognition in Realistic Sports Videos [M]//Moeslund T B, Thomas G, Hilton A. Computer Vision in Sports.Berlin: Springer, 2014: 181–208
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