Machine Learning-based Weight Estimation

Machine Learning-Based Weight Estimation is a computational approach within the domain of weight prediction that employs machine learning algorithms to model and estimate body weight from input features such as anthropometric measurements, medical imaging, or sensor-derived data, distinguished by its reliance on data-driven learning rather than rule-based or statistical modeling techniques.

100

Publications

3.2K

Citations

472

Authors

241

Institutions

Publications per year

2017–2026

72

Authors

472

  1. AR
    Alexey Ruchay

    Chelyabinsk State University, Russia

    4 publications · 141 citations

    4

    h-index

  2. CT
    Cem Tırınk

    Iğdır Üniversitesi, Türkiye

    3 publications · 126 citations

    3

    h-index

  3. VK
    Vladimir Kolpakov

    Federal Scientific Center for Biological Systems and Agricultural Technologies of the Russian Academy of Sciences, Russia

    3 publications · 117 citations

    3

    h-index

  4. HG
    Hao Guo

    China Agricultural University, China

    3 publications · 123 citations

    3

    h-index

  5. KD
    Konstantin Dorofeev

    Chelyabinsk State University, Russia

    3 publications · 117 citations

    3

    h-index

1–5 of 472

Venues

  1. Sensors

    8 publications · 211 citations

    8

    h-index

  2. Computers and Electronics in Agriculture

    4 publications · 174 citations

    4

    h-index

  3. Applied Sciences

    2 publications · 29 citations

    2

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 76 citations

    2

    h-index

  5. Animals

    2 publications · 56 citations

    2

    h-index

1–5