A review of machine learning in processing remote sensing data for mineral exploration

H Shirmard, E Farahbakhsh, RD Müller… - Remote Sensing of …, 2022 - Elsevier
The decline of the number of newly discovered mineral deposits and increase in demand for
different minerals in recent years has led exploration geologists to look for more efficient and …

Deep learning and its application in geochemical map**

R Zuo, Y **
Y Song, M Kalacska, M Gašparović, J Yao… - International Journal of …, 2023 - Elsevier
Geocomputation and geospatial artificial intelligence (GeoAI) have essential roles in
advancing geographic information science (GIS) and Earth observation to a new stage …

[HTML][HTML] GIS-based mineral prospectivity map** using machine learning methods: A case study from Tongling ore district, eastern China

T Sun, F Chen, L Zhong, W Liu, Y Wang - Ore Geology Reviews, 2019 - Elsevier
Predictive modelling of mineral prospectivity using GIS is a valid and progressively more
accepted tool for delineating reproducible mineral exploration targets. In this study, machine …

Intelligent map** of geochemical anomalies: Adaptation of DBSCAN and mean-shift clustering approaches

M Hajihosseinlou, A Maghsoudi… - Journal of Geochemical …, 2024 - Elsevier
Cluster analysis can be used to organize samples and generate ideas regarding the
multivariate geochemistry of given dataset. Traditional clustering techniques have the …

The processing methods of geochemical exploration data: past, present, and future

R Zuo, J Wang, Y **
J Yin, N Li - Ore geology reviews, 2022 - Elsevier
Abstract Machine learning algorithms have been widely applied in mineral prospectivity
map** (MPM). In this study, we implemented ensemble learning of extreme gradient …

Exploration information systems–A proposal for the future use of GIS in mineral exploration targeting

M Yousefi, OP Kreuzer, V Nykänen, JMA Hronsky - Ore Geology Reviews, 2019 - Elsevier
The advent of modern data collection and storage technologies has brought about a huge
increase in data volumes with both traditional and machine learning tools struggling to …

Random-drop data augmentation of deep convolutional neural network for mineral prospectivity map**

T Li, R Zuo, Y **ong, Y Peng - Natural Resources Research, 2021 - Springer
Convolutional neural network (CNN) has demonstrated promising performance in
classification and prediction in various fields. In this study, a CNN is used for mineral …

Fractal/multifractal modeling of geochemical data: A review

R Zuo, J Wang - Journal of Geochemical Exploration, 2016 - Elsevier
Over the past several decades, a wide range of complex structures or phenomena of interest
to geologists and geochemists has been quantitatively characterized using …