Machine Learning Based Range Prediction

Machine Learning Based Range Prediction is a computational framework within range estimation that employs machine learning algorithms to model and predict distance or spatial extent from sensor or environmental data, distinguishing itself from traditional rule-based or signal-processing techniques through its reliance on data-driven learning and generalization.

14

Publications

608

Citations

51

Authors

35

Institutions

Publications per year

2017–2026

7

Authors

51

  1. YW
    Yongxing Wang

    Beijing Jiaotong University, China

    3 publications · 167 citations

    3

    h-index

  2. JB
    Jun Bi

    Beijing Jiaotong University, China

    2 publications · 60 citations

    2

    h-index

  3. PG
    Paolo Gaudiano

    Boston University, United States

    1 publications · 29 citations

    1

    h-index

  4. CL
    Chaoru Lu

    Norwegian University of Science and Technology, Norway

    1 publications · 14 citations

    1

    h-index

  5. HL
    Hongwei Li

    University of Electronic Science and Technology of China, China

    1 publications · 38 citations

    1

    h-index

1–5 of 51

Venues

  1. Computers & Electrical Engineering

    1 publications · 81 citations

    1

    h-index

  2. Journal of Advanced Transportation

    1 publications · 107 citations

    1

    h-index

  3. Machine Learning

    1 publications · 29 citations

    1

    h-index

  4. IET Intelligent Transport Systems

    1 publications · 14 citations

    1

    h-index

  5. IEEE Access

    1 publications · 102 citations

    1

    h-index

1–5