Enhanced rock recognition via EVSS-integrated YOLO11: A deep learning approach for precise geological classification.
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| Title: | Enhanced rock recognition via EVSS-integrated YOLO11: A deep learning approach for precise geological classification. |
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| Authors: | Zhao F; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China.; BIM Technology Application Industry Research Center, Sichuan Communication Surveying and Design Institute, Chengdu, China., Leng X; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China.; College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu, China., Zhu M; BIM Technology Application Industry Research Center, Sichuan Communication Surveying and Design Institute, Chengdu, China., Luo S; College of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu, China., Huang J; State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China. |
| Source: | PloS one [PLoS One] 2026 Apr 24; Vol. 21 (4), pp. e0341862. Date of Electronic Publication: 2026 Apr 24 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0341862 |
