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

Authors

539

  1. YS
    Yuanming Shi

    ShanghaiTech University, China

    11 publications · 1.1K citations

    12

    h-index

  2. JZ
    Jun Zhang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    5 publications · 1.1K citations

    6

    h-index

  3. XC
    Xu Chen

    Sun Yat-sen University, China

    6 publications · 2.6K citations

    6

    h-index

  4. KY
    Kai Yang

    ShanghaiTech University, China

    5 publications · 620 citations

    5

    h-index

  5. ZZ
    Zhi Zhou

    Sun Yat-sen University, China

    5 publications · 1.2K citations

    5

    h-index

1–5 of 539

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 367 citations

    10

    h-index

  2. IEEE Transactions on Wireless Communications

    6 publications · 1.2K citations

    8

    h-index

  3. IEEE Internet of Things Journal

    5 publications · 1.4K citations

    5

    h-index

  4. 4

    h-index

  5. IEEE Access

    3 publications · 165 citations

    4

    h-index

1–5