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EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices

Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewer weights and shallower architectures than general DNNs.

Data and Resources

Cite this as

Liang Wang, Nan Zhang, Xiaoyang Qu, Jianzong Wang, Jiguang Wan, Guokuan Li, Kaiyu Hu, Guilin Jiang, Jing Xiao (2024). Dataset: EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices. https://doi.org/10.57702/nfqlu5a5

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2308.08717
Author Liang Wang
More Authors
Nan Zhang
Xiaoyang Qu
Jianzong Wang
Jiguang Wan
Guokuan Li
Kaiyu Hu
Guilin Jiang
Jing Xiao