Bayesian network classifiers for mineral potential mapping. - Alok Porwal; Emmanuel John M. Carranza; M. Hale (Comput. Geosci., 2006)

Abundance Estimation of Spectrally Similar Minerals by Using Derivative Spectra in Simulated Annealing. - Pravesh Debba; Emmanuel John M. Carranza; Freek D. van der Meer; Alfred Stein (IEEE Trans. Geosci. Remote. Sens., 2006)

Field Sampling from a Segmented Image. - Pravesh Debba; Alfred Stein; Freek D. van der Meer; Emmanuel John M. Carranza; Arko Lucieer (ICCSA (1), 2008)

Knowledge-guided data-driven evidential belief modeling of mineral prospectivity in Cabo de Gata, SE Spain. - Emmanuel John M. Carranza; Frank van Ruitenbeek; Chris A. Hecker; Mark van der Meijde; Freek D. van der Meer (Int. J. Appl. Earth Obs. Geoinformation, 2008)

Optimum Sampling Scheme for Characterization of Mine Tailings. - Pravesh Debba; Emmanuel John M. Carranza; Alfred Stein; Freek D. van der Meer (IGARSS (4), 2009)

Objective selection of suitable unit cell size in data-driven modeling of mineral prospectivity. - Emmanuel John M. Carranza (Comput. Geosci., 2009)

Algorithms for multi-parameter constrained compositing of borehole assay intervals from economic aspects. - Xiaogang Ma 001; Emmanuel John M. Carranza; Freek D. van der Meer; Chonglong Wu; Xialin Zhang (Comput. Geosci., 2010)

Development of a controlled vocabulary for semantic interoperability of mineral exploration geodata for mining projects. - Xiaogang Ma 001; Chonglong Wu; Emmanuel John M. Carranza; Ernst M. Schetselaar; Freek D. van der Meer; Gang Liu 003; Xinqing Wang; Xialin Zhang (Comput. Geosci., 2010)

Geocomputation of mineral exploration targets. - Emmanuel John M. Carranza (Comput. Geosci., 2011)

A SKOS-based multilingual thesaurus of geological time scale for interoperability of online geological maps. - Xiaogang Ma 001; Emmanuel John M. Carranza; Chonglong Wu; Freek D. van der Meer; Gang Liu 003 (Comput. Geosci., 2011)

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)

Application of geochemical zonality coefficients in mineral prospectivity mapping. - Mansour Ziaii; Emmanuel John M. Carranza; Mahdi Ziaei (Comput. Geosci., 2011)

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

Multi- and hyperspectral geologic remote sensing: A review. - Freek D. van der Meer; Harald van der Werff; Frank van Ruitenbeek; Chris A. Hecker; Wim H. Bakker; Marleen F. Noomen; Mark van der Meijde; Emmanuel John M. Carranza; J. Boudewijn de Smeth; Tsehaie Woldai (Int. J. Appl. Earth Obs. Geoinformation, 2012)

Ontology-aided annotation, visualization, and generalization of geological time-scale information from online geological map services. - Xiaogang Ma 001; Emmanuel John M. Carranza; Chonglong Wu; Freek D. van der Meer (Comput. Geosci., 2012)

Random forest predictive modeling of mineral prospectivity with small number of prospects and data with missing values in Abra (Philippines). - Emmanuel John M. Carranza; Alice G. Laborte (Comput. Geosci., 2015)

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping. - Mahyar Yousefi; Emmanuel John M. Carranza (Comput. Geosci., 2015)

Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. - Mahyar Yousefi; Emmanuel John M. Carranza (Comput. Geosci., 2015)

Geometric average of spatial evidence data layers: A GIS-based multi-criteria decision-making approach to mineral prospectivity mapping. - Mahyar Yousefi; Emmanuel John M. Carranza (Comput. Geosci., 2015)

GeoCube: A 3D mineral resources quantitative prediction and assessment system. - Ruixi Li; Gongwen Wang; Emmanuel John Muico Carranza (Comput. Geosci., 2016)

Performance evaluation of RBF- and SVM-based machine learning algorithms for predictive mineral prospectivity modeling: integration of S-A multifractal model and mineralization controls. - Reza Ghezelbash; Abbas Maghsoudi; Emmanuel John M. Carranza (Earth Sci. Informatics, 2019)

Integration of auto-encoder network with density-based spatial clustering for geochemical anomaly detection for mineral exploration. - Shuai Zhang; Keyan Xiao; Emmanuel John M. Carranza; Fan Yang 029; Zhicheng Zhao (Comput. Geosci., 2019)

Tensor-Based Low-Rank and Sparse Prior Information Constraints for Hyperspectral Image Denoising. - Guxi Wang; Hongwei Han; Emmanuel John M. Carranza; Si Guo; Ke Guo; Keyan Xiao (IEEE Access, 2020)

Optimization of geochemical anomaly detection using a novel genetic K-means clustering (GKMC) algorithm. - Reza Ghezelbash; Abbas Maghsoudi; Emmanuel John M. Carranza (Comput. Geosci., 2020)

A stacking methodology of machine learning for 3D geological modeling with geological-geophysical datasets, Laochang Sn camp, Gejiu (China). - Ran Jia; Yikai Lv; Gongwen Wang; Emmanuel John M. Carranza; Yongqing Chen; Chao Wei; Zhiqiang Zhang (Comput. Geosci., 2021)

First-Pass prospectivity mapping for Au-Ag mineralization in Sikhote-Alin Superterrane, Southeast Russia through field sampling, image enhancement on ASTER data, and MaxEnt modeling. - Sergei Shevyrev; Ekaterina V. Gorobeyko; Emmanuel John M. Carranza; Natalia G. Boriskina (Earth Sci. Informatics, 2023)

Infomax-based deep autoencoder network for recognition of multi-element geochemical anomalies linked to mineralization. - Saeid Esmaeiloghli; Seyed Hassan Tabatabaei; Emmanuel John M. Carranza (Comput. Geosci., 2023)

Spatial extrapolation of downscaled geochemical data using conditional GAN. - Xingnian Jiang; Xinqing Wang; Yue Liu; Emmanuel John M. Carranza; Shuyun Xie; Xiang Wan (Comput. Geosci., 2023)

A novel hybrid group method of data handling and Levenberg Marquardt model for estimating total organic carbon in source rocks with explainable artificial intelligence. - Christopher N. Mkono; Chuanbo Shen; Alvin K. Mulashani; Emmanuel John M. Carranza; Daud C. Kalibwami; Magori J. Nyangi (Eng. Appl. Artif. Intell., 2025)