IMRMB-Net: A lightweight student behavior recognition model for complex classroom scenarios.
With the continuous advancement of education informatization, classroom behavior analysis has become an important tool to improve teaching quality and student learning outcomes. However, student classroom behavior recognition methods still face challenges such as occlusion, small objects, and enviro...
Saved in:
| Main Authors: | Caihong Feng, Zheng Luo, Deyao Kong, Yunhong Ding, Jingyu Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0318817 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on lightweight pose estimation networks for classroom behavior recognition
by: XUE Tao, et al.
Published: (2024-12-01) -
A Method for Prediction and Analysis of Student Performance That Combines Multi-Dimensional Features of Time and Space
by: Zheng Luo, et al.
Published: (2024-11-01) -
DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network
by: Chunyu Dong, et al.
Published: (2025-04-01) -
An improved lightweight method based on EfficientNet for birdsong recognition
by: Haolun He, et al.
Published: (2025-07-01) -
Research on Calf Behavior Recognition Based on Improved Lightweight YOLOv8 in Farming Scenarios
by: Ze Yuan, et al.
Published: (2025-03-01)