Edge Inference
Edge Inference is a computational process in which machine learning models execute predictive or analytical tasks on data locally at the edge of the network, within constrained IoT edge devices or gateways, to minimize latency, bandwidth usage, and cloud dependency while enabling real-time decision-making.
154
Publications
11.3K
Citations
539
Authors
198
Institutions
Publications per year
2017–2026
146
154
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 154
539
12
h-index
Hong Kong University of Science and Technology, Hong Kong SAR China
5 publications · 1.1K citations
6
h-index
6
h-index
5
h-index
5
h-index
1–5 of 539
198
ShanghaiTech University
Shanghai, China
11 h-index
28 publications
3K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
9 h-index
16 publications
2.5K citations
Tsinghua University
Beijing, China
9 h-index
23 publications
1.5K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
7 h-index
10 publications
484 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
7 h-index
9 publications
1.6K citations

Sun Yat-sen University
Guangzhou, China
6 h-index
19 publications
5.9K citations
University of Chinese Academy of Sciences
Beijing, China
5 h-index
5 publications
609 citations

Huazhong University of Science and Technology
Wuhan, China
4 h-index
8 publications
1.2K citations
1–8 of 198
Repository · 10 publications · 367 citations
10
h-index
6 publications · 1.2K citations
8
h-index
5 publications · 1.4K citations
5
h-index
3 publications · 442 citations
4
h-index
3 publications · 165 citations
4
h-index
1–5