Mineral Image Classification

Mineral Image Classification is a computational method in machine vision that categorizes mineral species based on their visual characteristics extracted from digital imagery, distinguishing itself by integrating domain-specific spectral, textural, and morphological features for automated mineralogical analysis in mining applications.

239

Publications

12.6K

Citations

779

Authors

328

Institutions

Publications per year

2017–2026

138

Authors

779

  1. RZ
    Renguang Zuo

    China University of Geosciences, China

    14 publications · 1.6K citations

    14

    h-index

  2. EJ
    Emmanuel John M. Carranza

    James Cook University, Australia

    12 publications · 1.8K citations

    12

    h-index

  3. YX
    Yihui Xiong

    China University of Geosciences, China

    9 publications · 827 citations

    9

    h-index

  4. FY
    Fanfan Yang

    China University of Geosciences, China

    4 publications · 143 citations

    4

    h-index

  5. GW
    Gongwen Wang

    China University of Geosciences (Beijing), China

    4 publications · 136 citations

    4

    h-index

1–5 of 779

Venues

  1. Computers & Geosciences

    CAGEO · 25 publications · 2.7K citations

    21

    h-index

  2. Natural Resources Research

    NRR · 17 publications · 963 citations

    17

    h-index

  3. Minerals Engineering

    14 publications · 524 citations

    14

    h-index

  4. Ore Geology Reviews

    7 publications · 779 citations

    7

    h-index

  5. Minerals

    7 publications · 125 citations

    7

    h-index

1–5