(Accepted Version) Online First Publishing Date: 2023-02-28 10:15:13Online First Certificate Download
Research on lithology identification method of rock thin section images based on MobileViTChinese Full TextEnglish Full Text (MT)
Wang Qiong;Yang Jie;Huo Fengcai;Dong Hongli;Ren Weijian;Yu Tao;
Abstract: The rock thin-section images contain a large amount of geological feature information that cannot be observed with the naked eye. The lithology identification of rock thin-section images lays the foundation for subsequent oil exploration and production. Aiming at the problems of unbalanced lithology identification data set and many identification model parameters, an improved lightweight MobileViT model is proposed to model and analyze the rock slice images covering more than 90% of common litho... More
- Series:
(A) Mathematics/ Physics/ Mechanics/ Astronomy; (B) Chemistry/ Metallurgy/ Environment/ Mine Industry
- Subject:
Geology; Petroleum, Natural Gas Industry
- Classification Code:
P618.13
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