Segmentation of digital rock images using deep convolutional autoencoder networks

Segmentation is a critical step in Digital Rock Physics (DRP) as the original images are available in a gray-scale format. Conventional methods often use thresholding to delineate distinct phases and, consequently, watershed algorithm to identify the existing phases. Such methods are based on color...

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Veröffentlicht in:	Computers & geosciences Jg. 126; S. 142 - 150
Hauptverfasser:	Karimpouli, Sadegh, Tahmasebi, Pejman
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.05.2019
Schlagworte:	algorithms Artificial intelligence color computers data collection Digital rock physics (DRP) Mineral identification neural networks sandstone Segmentation Segmentation Mineral identification Artificial intelligence Digital rock physics (DRP)
ISSN:	0098-3004
Online-Zugang:	Volltext
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