Crowd counting at the edge using weighted knowledge distillation
Abstract Visual crowd counting has gained serious attention during the last couple of years. The consistent contributions to this topic have now solved several inherited challenges such as scale variations, occlusions, and cross-scene applications. However, these works attempt to improve accuracy an...
Saved in:
| Main Authors: | Muhammad Asif Khan, Hamid Menouar, Ridha Hamila, Adnan Abu-Dayya |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-90750-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Crowd Counting Framework Combining with Crowd Location
by: Jin Zhang, et al.
Published: (2021-01-01) -
Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing
by: Arief Setyanto, et al.
Published: (2025-01-01) -
ClassRoom-Crowd: A Comprehensive Dataset for Classroom Crowd Counting and Cross-Domain Baseline Analysis
by: Wenqian Jiang, et al.
Published: (2025-02-01) -
Label Noise Robust Crowd Counting with Loss Filtering Factor
by: Zhengmeng Xu, et al.
Published: (2024-12-01) -
Diverse Representation Knowledge Distillation for Efficient Edge AI Teledermatology in Skin Disease Diagnosis
by: Andreas Winata, et al.
Published: (2025-01-01)