Data-driven Mineral Prospectivity Mapping by Joint Application of Unsupervised Convolutional Auto-encoder Network and Supervised Convolutional Neural NetworkShuai Zhang, Xu Yang, Emmanuel John M. Carranza et al.|Natural Resources Research|2021Cited by 116
Integration of auto-encoder network with density-based spatial clustering for geochemical anomaly detection for mineral explorationShuai Zhang, Zhicheng Zhao, Keyan Xiao et al.|Computers & Geosciences|2019Cited by 70
Mineral Prospectivity Mapping based on Isolation Forest and Random Forest: Implication for the Existence of Spatial Signature of Mineralization in OutliersShuai Zhang, Jie Xiang, Zhenghui Chen et al.|Natural Resources Research|2021Cited by 65
Maximum Entropy and Random Forest Modeling of Mineral Potential: Analysis of Gold Prospectivity in the Hezuo–Meiwu District, West Qinling Orogen, ChinaShuai Zhang, Fan Yang, Keyan Xiao et al.|Natural Resources Research|2018Cited by 61
Geochemically Constrained Prospectivity Mapping Aided by Unsupervised Cluster AnalysisShuai Zhang, Xu Yang, Emmanuel John M. Carranza et al.|Natural Resources Research|2021Cited by 33