Localization Learning

Localization Learning is a computational framework within spatial localization that integrates sensor data and environmental context to enable a system to autonomously acquire and refine positional awareness through experience-driven adaptation.

95

Publications

4.7K

Citations

322

Authors

140

Institutions

Publications per year

2017–2026

44

Authors

322

  1. TS
    Thad Starner

    Georgia Institute of Technology, United States

    2 publications · 1.1K citations

    2

    h-index

  2. WM
    Weimin Mou

    University of Alberta, Canada

    2 publications · 57 citations

    2

    h-index

  3. SY
    Seung-kook Yun

    Massachusetts Institute of Technology, United States

    2 publications · 82 citations

    2

    h-index

  4. RS
    Ruslan Salakhutdinov

    Carnegie Mellon University, United States

    2 publications · 70 citations

    2

    h-index

  5. YS
    Y. S. Ivanov

    Main Astronomical Observatory, Ukraine

    2 publications · 43 citations

    2

    h-index

1–5 of 322

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 76 citations

    4

    h-index

  2. Neurocomputing

    3 publications · 363 citations

    3

    h-index

  3. Vision Research

    3 publications · 211 citations

    3

    h-index

  4. PLoS ONE

    3 publications · 69 citations

    3

    h-index

  5. IEEE Transactions on Mobile Computing

    TMCCI · 3 publications · 136 citations

    3

    h-index

1–5