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Dataset in support of the journal paper 'Predictive Visualisation of Fibre Laser Cutting Topography via Deep Learning with Image Inpainting'

Dataset in support of the journal paper 'Predictive Visualisation of Fibre Laser Cutting Topography via Deep Learning with Image Inpainting'
Dataset in support of the journal paper 'Predictive Visualisation of Fibre Laser Cutting Topography via Deep Learning with Image Inpainting'
This dataset contains: A method figure, examples images for experimental and predicted topography sections, as well as examples for a topography inpainting visualisation cGAN. There is also a demonstration of the application of inpainting to increae the size of experimental topographies, as well as using inpainting to predict the appearance of defects between different cutting speeds. There is also a regression plot comparing experimental and predicted labels for a CNN and a collection of histograms and plots comparing the statistical distributions of experimental and inpainted topographic sections, with their respective numerical datasets.
University of Southampton
Courtier, Alexander
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Praeger, Matthew
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Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Codemard, Christophe A.
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Harrison, Paul
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Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
Zervas, Michalis N.
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Courtier, Alexander
0a50732a-ef3f-4042-82f4-9b573c8c9ee8
Praeger, Matthew
84575f28-4530-4f89-9355-9c5b6acc6cac
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Codemard, Christophe A.
0a7db5d9-507e-41e3-88bb-2606402f558b
Harrison, Paul
992a7c06-5d61-4591-8455-f6530d5faa6c
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
Zervas, Michalis N.
26d5ccd0-3c9e-45fa-93c4-08366b2dcd85

Courtier, Alexander and Harrison, Paul (2022) Dataset in support of the journal paper 'Predictive Visualisation of Fibre Laser Cutting Topography via Deep Learning with Image Inpainting'. University of Southampton doi:10.5258/SOTON/D2489 [Dataset]

Record type: Dataset

Abstract

This dataset contains: A method figure, examples images for experimental and predicted topography sections, as well as examples for a topography inpainting visualisation cGAN. There is also a demonstration of the application of inpainting to increae the size of experimental topographies, as well as using inpainting to predict the appearance of defects between different cutting speeds. There is also a regression plot comparing experimental and predicted labels for a CNN and a collection of histograms and plots comparing the statistical distributions of experimental and inpainted topographic sections, with their respective numerical datasets.

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Read_Me.txt - Dataset
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Datasets.zip - Dataset
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Figures.zip - Dataset
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More information

Published date: 17 December 2022

Identifiers

Local EPrints ID: 478051
URI: http://eprints.soton.ac.uk/id/eprint/478051
PURE UUID: 63c889d9-61fb-4570-8c7d-27d72d53b0c0
ORCID for Alexander Courtier: ORCID iD orcid.org/0000-0003-1943-4055
ORCID for Matthew Praeger: ORCID iD orcid.org/0000-0002-5814-6155
ORCID for James Grant-Jacob: ORCID iD orcid.org/0000-0002-4270-4247
ORCID for Benjamin Mills: ORCID iD orcid.org/0000-0002-1784-1012

Catalogue record

Date deposited: 21 Jun 2023 16:39
Last modified: 06 Jun 2024 02:07

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Contributors

Creator: Alexander Courtier ORCID iD
Contributor: Matthew Praeger ORCID iD
Contributor: James Grant-Jacob ORCID iD
Contributor: Christophe A. Codemard
Creator: Paul Harrison
Contributor: Benjamin Mills ORCID iD
Contributor: Michalis N. Zervas

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