Tomography data of methane-bearing sand used to investigate U-Net segmentation methods
Tomography data of methane-bearing sand used to investigate U-Net segmentation methods
These tomographic data sets were used to evaluate the suitability of different U-Net implementations to produce accurate segmentations. Hand-annotated training and validation sub-volumes as well as the segmentation outputs from the U-Net implementations are also included. These data support a research article submission titled: U-Net Segmentation Methods for Variable-Contrast XCT Images of Methane-Bearing Sand. All data processing methods are described in the article manuscript and supporting information.
Alvarez Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
King, Oliver
2bfc86d6-849f-4725-9ae5-abb96fb8868d
Bangalore Narasimha Murthy, Madhusudhan
e139e3d3-2992-4579-b3f0-4eec3ddae98c
Connolley, Thomas
baeb481e-885f-4ac9-ad83-fc6537ac5337
Basham, Mark
55739b97-162a-4d37-bee8-a392948fcbcc
Ahmed, Sharif
ddc6bab1-9d76-4391-b7ea-ae68d6f3924d
Alvarez Borges, Fernando
5512cdfd-6ad3-475f-8aec-2fc767607314
King, Oliver
2bfc86d6-849f-4725-9ae5-abb96fb8868d
Bangalore Narasimha Murthy, Madhusudhan
e139e3d3-2992-4579-b3f0-4eec3ddae98c
Connolley, Thomas
baeb481e-885f-4ac9-ad83-fc6537ac5337
Basham, Mark
55739b97-162a-4d37-bee8-a392948fcbcc
Ahmed, Sharif
ddc6bab1-9d76-4391-b7ea-ae68d6f3924d
Alvarez Borges, Fernando
(2021)
Tomography data of methane-bearing sand used to investigate U-Net segmentation methods.
Zenodo
http://doi.org/10.5281/zenodo.4580278
[Dataset]
Abstract
These tomographic data sets were used to evaluate the suitability of different U-Net implementations to produce accurate segmentations. Hand-annotated training and validation sub-volumes as well as the segmentation outputs from the U-Net implementations are also included. These data support a research article submission titled: U-Net Segmentation Methods for Variable-Contrast XCT Images of Methane-Bearing Sand. All data processing methods are described in the article manuscript and supporting information.
This record has no associated files available for download.
More information
Published date: 2021
Identifiers
Local EPrints ID: 474064
URI: http://eprints.soton.ac.uk/id/eprint/474064
DOI: http://doi.org/10.5281/zenodo.4580278
PURE UUID: 5dfe9f03-1faf-443b-a39d-a35a6d8a16f9
Catalogue record
Date deposited: 10 Feb 2023 17:34
Last modified: 06 May 2023 02:05
Export record
Altmetrics
Contributors
Creator:
Fernando Alvarez Borges
Contributor:
Oliver King
Research team head:
Thomas Connolley
Contributor:
Mark Basham
Contributor:
Sharif Ahmed
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics