Joint Adaptive Resolution Selection and Conditional Early Exiting for Efficient Video Recognition on Edge Devices
Given the explosive growth in video content generation, there is a rising demand for efficient and scalable video recognition. Deep learning has shown its remarkable performance in video analytics, by applying 2D or 3D Convolutional Neural Networks (CNNs) across multiple video frames. However, high...
Saved in:
| Main Authors: | Qingli Wang, Chengwu Yu, Shan Chen, Weiwei Fang, Naixue Xiong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2025-05-01
|
| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2024.9020093 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analysis of the Decision to Make a Business Exit in Small and Medium Enterprises (SMES)
by: Novita Ratna Satiti
Published: (2024-12-01) -
Distributed model cache-driven device-cloud collaboration in adaptive video analytics
by: LIAO Tianjun, et al.
Published: (2025-05-01) -
System and application of video surrveillance based on edge computing
by: Sanming PAN, et al.
Published: (2020-06-01) -
Privacy-Preserving Live Video Analytics for Drones via Edge Computing
by: Piyush Nagasubramaniam, et al.
Published: (2024-11-01) -
A simulation study of the influence of dedicated building exits on the evacuation patterns of vulnerable populations
by: Yu Qiao, et al.
Published: (2024-01-01)