Determination of the air void content of asphalt concrete mixtures using artificial intelligence techniques to segment micro-CT images-Reference-Cited by-同舟云学术

Determination of the air void content of asphalt concrete mixtures using artificial intelligence techniques to segment micro-CT images

Published:2021-07-15 Issue: Volume: Page:1-10
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Enríquez-León Alexis Jair¹^ORCID,de Souza Thiago Delgado¹^ORCID,Aragão Francisco Thiago Sacramento¹^ORCID,Braz Delson²^ORCID,Pereira André Maués Brabo³^ORCID,Nogueira Liebert Parreiras⁴^ORCID

Affiliation:

1. Civil Engineering Program – COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

2. Nuclear Engineering Program – COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

3. Institute of Computing, Fluminense Federal University, Rio de Janeiro, Brazil

4. Department of Biomaterials, University of Oslo, Oslo, Norway

Funder

CAPES

CNPq

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2021.1931197

Reference31 articles.

1. Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification

2. Porosity Characterization of Iron Ore Pellets by X-Ray Microtomography

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