Image-based Lithology Classification
Image-Based Lithology Classification is a computational method that identifies and categorizes rock types from visual data by analyzing pixel-level features and spatial patterns in geological images through machine learning or deep learning techniques.
94
Publications
4K
Citations
337
Authors
139
Institutions
Publications per year
2017–2026
72
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139

China University of Petroleum, Beijing
Beijing, China
6 h-index
22 publications
1.6K citations

Hohai University
Nanjing, China
6 h-index
26 publications
1.5K citations
University of Chile
Santiago, Chile
4 h-index
18 publications
600 citations
China University of Geosciences
Wuhan, China
4 h-index
18 publications
524 citations

Shiraz University
Shiraz, Iran
4 h-index
8 publications
194 citations
Shandong University
Jinan, China
3 h-index
11 publications
1.1K citations
Shandong Transportation Research Institute
Jinan, China
3 h-index
5 publications
272 citations

China National Petroleum Corporation (China)
Beijing, China
3 h-index
2 publications
94 citations
1–8 of 139
10 publications · 901 citations
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5 publications · 191 citations
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4 publications · 121 citations
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2 publications · 41 citations
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3 publications · 71 citations
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