Image-based Quality Grading

Image-Based Quality Grading is a computational method in agricultural engineering that uses digital image analysis to objectively assess and classify the external quality attributes of fruits, such as size, color, shape, and surface defects, by applying machine vision algorithms to differentiate produce according to standardized grading criteria.

150

Publications

6.4K

Citations

478

Authors

170

Institutions

Publications per year

2017–2026

61

Authors

478

  1. NK
    Naoshi Kondo

    Kyoto University, Japan

    5 publications · 202 citations

    5

    h-index

  2. KR
    Kavindra R. Jain

    Indian Institute of Toxicology Research, India

    3 publications · 42 citations

    3

    h-index

  3. AS
    Amund Skavhaug

    SINTEF, Norway

    3 publications · 89 citations

    3

    h-index

  4. CK
    Chintan K. Modi

    Patel Hospital, India

    3 publications · 42 citations

    3

    h-index

  5. KN
    Kazunori Ninomiya

    Kyoto University, Japan

    3 publications · 32 citations

    3

    h-index

1–5 of 478

Venues

  1. Computers and Electronics in Agriculture

    8 publications · 533 citations

    8

    h-index

  2. Transactions of the ASAE

    5 publications · 333 citations

    5

    h-index

  3. Journal of Food Engineering

    4 publications · 290 citations

    4

    h-index

  4. International Journal of Computer Applications

    4 publications · 220 citations

    4

    h-index

  5. Journal of Food Process Engineering

    3 publications · 96 citations

    3

    h-index

1–5