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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Vydané v:	Applied geochemistry Ročník 122; s. 104710
Hlavní autori:	Luo, Zijing, Xiong, Yihui, Zuo, Renguang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.11.2020
Predmet:	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
On-line prístup:	Získať plný text
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