Recognition of geochemical anomalies using a deep variational autoencoder network

Deep learning (DL) algorithms have received increased attention in various fields. In the field of geoscience, DL has been shown to be a powerful tool for mining complex, high-level, and non-linear geospatial data and for extracting previously unknown patterns related to geological processes. In thi...

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Bibliographic Details
Published in:	Applied geochemistry Vol. 122; p. 104710
Main Authors:	Luo, Zijing, Xiong, Yihui, Zuo, Renguang
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2020
Subjects:	algorithms China copper Deep learning ferric oxide Geochemical mapping geochemistry iron lead manganese Mineral exploration mineralization mining probability spatial data Variational autoencoder network zinc China Deep learning Mineral exploration Geochemical mapping Variational autoencoder network
ISSN:	0883-2927, 1872-9134
Online Access:	Get full text
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