Edge Ai Inference
Edge AI Inference is a computational process in which a trained artificial intelligence model performs real-time decision-making or prediction at the network edge, distinguished from cloud-based inference by its execution on resource-constrained, geographically distributed edge devices to minimize latency, bandwidth usage, and privacy exposure.
93
Publications
8.9K
Citations
508
Authors
185
Institutions
Publications per year
2017–2026
92
Parents
93
Scaling for edge inference of deep neural networks
Xiaowei Xu, Yukun Ding, Xiaobo Sharon Hu et al. · Nature Electronics · 2018 · 469 citations
Machine Learning at Facebook: Understanding Inference at the Edge
Carole-Jean Wu, David Brooks, Kevin Chen et al. · 2019 · 448 citations
1–5 of 93
508
7
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
4 publications · 1.2K citations
4
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
4 publications · 689 citations
4
h-index
3
h-index
3
h-index
1–5 of 508
185

Hong Kong Polytechnic University
Hong Kong, Hong Kong
7 h-index
10 publications
1.5K citations
ShanghaiTech University
Shanghai, China
7 h-index
18 publications
2.8K citations
Peng Cheng Laboratory
Shenzhen, China
5 h-index
5 publications
1.4K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
4 h-index
6 publications
257 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
4 h-index
4 publications
847 citations

Zhejiang University
Hangzhou, China
3 h-index
11 publications
1.4K citations
Swinburne University of Technology
Melbourne, Australia
3 h-index
5 publications
330 citations

University of Electronic Science and Technology of China
Chengdu, China
3 h-index
4 publications
577 citations
1–8 of 185
Repository · 7 publications · 148 citations
7
h-index
4 publications · 1.1K citations
4
h-index
3 publications · 1.1K citations
3
h-index
2 publications · 189 citations
2
h-index
2 publications · 154 citations
2
h-index
1–5