Pretraining Techniques for Steel Surface Roughness Prediction with Long Thin Spatial Industrial Data

Journal article 382 views 139 downloads

ALEXANDER MILNE, Xianghua Xie

, Gary Tam

Lecture Notes in Computer Science, Volume: 15656, Pages: 302 - 314

Swansea University Authors: ALEXANDER MILNE, Xianghua Xie , Gary Tam

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Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention).
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DOI (Published version): 10.1007/978-3-032-07343-3_24

Published in:	Lecture Notes in Computer Science
ISBN:	9783032073426 9783032073433
ISSN:	0302-9743 1611-3349
Published:	Cham Springer Nature Switzerland 2026
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa69563

Keywords:	Representation learning; High-aspect-ratio images; Pretext task; Contrastive learning; Autoencoder
College:	Faculty of Science and Engineering
Funders:	This work was funded by EPSRC Industrial Case award (EP/V519601/1). For the purpose of open access the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.
Start Page:	302
End Page:	314