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researcher

M. Grédiac

2 papers here

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

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • eess.IV1
  • physics.class-ph1

identity via Semantic Scholar / OpenAlex

most citedWhen Deep Learning Meets Digital Image Correlation

157 citations · 158 across the 2 of their papers we have counts for

collaborators

2 papers

eess.IV2020★ 157 cited

When Deep Learning Meets Digital Image Correlation

S. Boukhtache, K. Abdelouahab, F. Berry +3

Convolutional Neural Networks (CNNs) constitute a class of Deep Learning models which have been used in the recent past to resolve many problems in computer vision, in particular o…

physics.class-ph2019★ 1 cited

Identification of Constitutive Parameters Governing the Hyperelastic Response of Rubber by Using Full-field Measurement and the Virtual Fields Method

A Tayeb, Jean-Benoit Le Cam, M. Grédiac +4

In this study, the Virtual Fields Method (VFM) is applied to identify constitutive parameters of hyperelastic models from a heterogeneous test. Digital image correlation (DIC) was…

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