Fractal characterization of the spatial distribution of geological point processes. - Renguang Zuo; Frederik P. Agterberg; Qiuming Cheng; Lingqing Yao (Int. J. Appl. Earth Obs. Geoinformation, 2009)

Mapping complexity of spatial distribution of faults using fractal and multifractal models: vectoring towards exploration targets. - Jiangnan Zhao; Shouyu Chen; Renguang Zuo; Emmanuel John M. Carranza (Comput. Geosci., 2011)

Support vector machine: A tool for mapping mineral prospectivity. - Renguang Zuo; Emmanuel John M. Carranza (Comput. Geosci., 2011)

A MATLAB-based program for processing geochemical data using fractal/multifractal modeling. - Jian Wang; Renguang Zuo (Earth Sci. Informatics, 2015)

Recognition of geochemical anomalies using a deep autoencoder network. - Yihui Xiong; Renguang Zuo (Comput. Geosci., 2016)

Identification of geochemical anomalies through combined sequential Gaussian simulation and grid-based local singularity analysis. - Jian Wang; Renguang Zuo (Comput. Geosci., 2018)

GIS-based rare events logistic regression for mineral prospectivity mapping. - Yihui Xiong; Renguang Zuo (Comput. Geosci., 2018)

A fractal model of granitic intrusion and variability based on cellular automata. - Yihui Xiong; Renguang Zuo; Keith C. Clarke (Comput. Geosci., 2019)

Decomposing the Long-term Variation in Population Exposure to Outdoor PM2.5 in the Greater Bay Area of China Using Satellite Observations. - Changqing Lin; Alexis Kai-Hon Lau; Jimmy C. H. Fung; Qianshan He; Jun Ma; Xingcheng Lu; Zhiyuan Li; Chengcai Li; Renguang Zuo; Andromeda H. S. Wong (Remote. Sens., 2019)

Mapping Himalayan leucogranites using a hybrid method of metric learning and support vector machine. - Ziye Wang; Renguang Zuo; Yanni Dong (Comput. Geosci., 2020)

Recognizing multivariate geochemical anomalies for mineral exploration by combining deep learning and one-class support vector machine. - Yihui Xiong; Renguang Zuo (Comput. Geosci., 2020)

Mapping of Himalaya Leucogranites Based on ASTER and Sentinel-2A Datasets Using a Hybrid Method of Metric Learning and Random Forest. - Ziye Wang; Renguang Zuo; Yanni Dong (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020)

Spatial modelling of hydrothermal mineralization-related geochemical patterns using INLA+SPDE and local singularity analysis. - Jian Wang; Renguang Zuo (Comput. Geosci., 2021)

A positive and unlabeled learning algorithm for mineral prospectivity mapping. - Yihui Xiong; Renguang Zuo (Comput. Geosci., 2021)

Analysis of Temporal and Spatial Characteristics of Urban Expansion in Xiaonan District from 1990 to 2020 Using Time Series Landsat Imagery. - Yan Liu; Renguang Zuo; Yanni Dong (Remote. Sens., 2021)

Lithological Mapping Based on Fully Convolutional Network and Multi-Source Geological Data. - Ziye Wang; Renguang Zuo; Hao Liu (Remote. Sens., 2021)

Mineral prospectivity mapping using a joint singularity-based weighting method and long short-term memory network. - Ziye Wang; Renguang Zuo (Comput. Geosci., 2022)

A geologically-constrained deep learning algorithm for recognizing geochemical anomalies. - Chunjie Zhang; Renguang Zuo; Yihui Xiong; Xinfu Zhao; Kuidong Zhao (Comput. Geosci., 2022)

Construction Land Information Extraction and Expansion Analysis of Xiaogan City Using One-Class Support Vector Machine. - Jaxin Nie; Yanni Dong; Renguang Zuo (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Geological Mapping via Convolutional Neural Network Based on Remote Sensing and Geochemical Survey Data in Vegetation Coverage Areas. - Ting Pan; Renguang Zuo; Ziye Wang (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Fusion of GaoFen-5 and Sentinel-2B data for lithological mapping using vision transformer dynamic graph convolutional network. - Yanni Dong; Zhenzhen Yang; Quanwei Liu; Renguang Zuo; Ziye Wang (Int. J. Appl. Earth Obs. Geoinformation, 2024)

An Evaluation of Convolutional Neural Networks for Lithological Mapping Based on Hyperspectral Images. - Ziye Wang; Renguang Zuo (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration. - Renguang Zuo; Ying Xu (Comput. Geosci., 2024)

Geological-knowledge-guided graph self-supervised pretraining framework for identifying mineralization-related geochemical anomalies. - Zhiyi Chen; Renguang Zuo (Comput. Geosci., 2025)