Machine Learning Crop Classification

Machine Learning Crop Classification is a computational methodology that employs machine learning algorithms to categorize crops in agricultural landscapes based on remotely sensed data, distinguishing itself from traditional classification techniques through its capacity to autonomously learn and adapt discriminative patterns from large, complex datasets.

585

Publications

32.5K

Citations

2.3K

Authors

801

Institutions

Publications per year

2017–2026

506

Authors

2.3K

  1. MK
    Murat Köklü

    Selçuk University, Türkiye

    7 publications · 562 citations

    7

    h-index

  2. NK
    Nataliia Kussul

    Space Research Institute, Ukraine

    6 publications · 285 citations

    6

    h-index

  3. AY
    Ali Yaşar

    Selçuk University, Türkiye

    5 publications · 127 citations

    5

    h-index

  4. VK
    Vinay Kukreja

    Chitkara University, India

    5 publications · 428 citations

    5

    h-index

  5. LD
    Liping Di

    George Mason University, United States

    5 publications · 384 citations

    5

    h-index

1–5 of 2.3K

Venues

  1. Computers and Electronics in Agriculture

    36 publications · 4.3K citations

    31

    h-index

  2. Remote Sensing

    21 publications · 1.2K citations

    18

    h-index

  3. Multimedia Tools and Applications

    16 publications · 696 citations

    14

    h-index

  4. International Journal of Remote Sensing

    11 publications · 684 citations

    11

    h-index

  5. Agronomy

    11 publications · 706 citations

    10

    h-index

1–5