Knowledge Network Node
(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

CNKI exclusive online-first articles is prohibited to reprint and excerpt without permission.

Download the mobile appuse the app to scan this coderead the article.

Tips: Please download CAJViewer to view CAJ format full text.

Download: 889 Pagecount: 11 Size: 1227K

Related Literature
  • Similar Article
  • Reader Recommendation
  • Associated Author