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
Parents
239
1–5 of 239
779
14
h-index
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1–5 of 779
328
China University of Geosciences
Wuhan, China
18 h-index
60 publications
4.8K citations

China University of Geosciences (Beijing)
Beijing, China
13 h-index
35 publications
1.6K citations

China Geological Survey
Beijing, China
10 h-index
27 publications
1.1K citations

Central South University
Changsha, China
6 h-index
22 publications
1.3K citations

Northeastern University
Shenyang, China
5 h-index
17 publications
752 citations

Chinese Academy of Geological Sciences
Beijing, China
5 h-index
17 publications
1.1K citations
Amirkabir University of Technology
Tehran, Iran
5 h-index
12 publications
640 citations
Ministry of Natural Resources
Beijing, China
5 h-index
10 publications
554 citations
1–8 of 328
CAGEO · 25 publications · 2.7K citations
21
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NRR · 17 publications · 963 citations
17
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14 publications · 524 citations
14
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7 publications · 779 citations
7
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7 publications · 125 citations
7
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