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首页|期刊导航|Artificial Intelligence in Geosciences|Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data:A case study in Luoping county,Yunnan,China

Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data:A case study in Luoping county,Yunnan,China

Gong Cheng Syed Hussain Yingdong Yang Li Sun Asad Atta Cheng Huang Guangqiang Li Mohammad Naseer Lingyi Liao

Artificial Intelligence in Geosciences2026,Vol.7Issue(1):P.16-29,14.
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Artificial Intelligence in Geosciences2026,Vol.7Issue(1):P.16-29,14.DOI:10.1016/j.aiig.2025.100163

Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data:A case study in Luoping county,Yunnan,China

Gong Cheng 1Syed Hussain 2Yingdong Yang 3Li Sun 4Asad Atta 5Cheng Huang 3Guangqiang Li 1Mohammad Naseer 1Lingyi Liao1

作者信息

  • 1. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring,Ministry of Education,School of Geosciences and Info-Physics,Central South University,Changsha,410083,China
  • 2. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring,Ministry of Education,School of Geosciences and Info-Physics,Central South University,Changsha,410083,China State Key Laboratory of Deep Earth and Mineral Exploration,Institute of Mineral Resources,Chinese Academy of Geological Sciences,Beijing,100037,China
  • 3. Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area,MNR,Yunnan Key Laboratory of Geohazard Forecast and Geoecological Restoration in Plateau Mountainous Area,Yunnan Institute of Geological Environment Monitoring,Kunming,Yunnan,650216,China
  • 4. State Key Laboratory of Deep Earth and Mineral Exploration,Institute of Mineral Resources,Chinese Academy of Geological Sciences,Beijing,100037,China
  • 5. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring,Ministry of Education,School of Geosciences and Info-Physics,Central South University,Changsha,410083,China GIS Lab Punjab Forest Department Lahore,Pakistan
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摘要

关键词

Fault detection/Imbalance datasets/Focal loss function/CHRRA-Unet/Hrrformer models/Remote sensing data

分类

天文与地球科学

引用本文复制引用

Gong Cheng,Syed Hussain,Yingdong Yang,Li Sun,Asad Atta,Cheng Huang,Guangqiang Li,Mohammad Naseer,Lingyi Liao..Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data:A case study in Luoping county,Yunnan,China[J].Artificial Intelligence in Geosciences,2026,7(1):P.16-29,14.

基金项目

funded by Comprehensive Remote Sensing for Refined Investigation and Risk Assessment of Geological Hazards in Yunnan Province,grant number YCZH[2020]-68 and The APC was funded by Construction of Yunnan Geological Hazard Identification Center,YCZH[2021]-23 and Fine investigation and risk assessment of geological hazards in key regions of Yunnan Province,YNGH[2021]-168F.Also support was provided by the Chinese Academy of Geological Sciences Basal Research Fund(No.JKYDM2025110) (No.JKYDM2025110)

the Open Project Program of Hebei Province Collaborative Innovation Center for Strategic Critical Mineral Research,Hebei GEO University(No.HGUXT-2024-1) (No.HGUXT-2024-1)

the Geological Survey Project of the China Geological Survey(DD20230366) (DD20230366)

the Open Project of the Technology Innovation Center for Deep Gold Resources Exploration and Mining,Ministry of Natural Resources(No.LDKF-2023BZX-20). (No.LDKF-2023BZX-20)

Artificial Intelligence in Geosciences

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