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W. Nash

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cond-mat.mtrl-sci1
  • cs.HC1

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedRustSEG -- Automated segmentation of corrosion using deep learning

14 citations · 14 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 14 cited

RustSEG -- Automated segmentation of corrosion using deep learning

B. Burton, W. T. Nash, N. Birbilis

The inspection of infrastructure for corrosion remains a task that is typically performed manually by qualified engineers or inspectors. This task of inspection is laborious, slow,…

cond-mat.mtrl-sci2022

cardiGAN: A Generative Adversarial Network Model for Design and Discovery of Multi Principal Element Alloys

Z. Li, W. T. Nash, S. P. O Brien +3

Multi-principal element alloys (MPEAs), inclusive of high entropy alloys (HEAs), continue to attract significant research attention owing to their potentially desirable properties.…

cs.HC2019

Automated Corrosion Detection Using Crowd Sourced Training for Deep Learning

W. T. Nash, C. J. Powell, T. Drummond +1

The automated detection of corrosion from images (i.e., photographs) or video (i.e., drone footage) presents significant advantages in terms of corrosion monitoring. Such advantage…

cs.CV2018

Quantity beats quality for semantic segmentation of corrosion in images

Will Nash, Tom Drummond, Nick Birbilis

Dataset creation is typically one of the first steps when applying Artificial Intelligence methods to a new task; and the real world performance of models hinges on the quality and…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.