Open‐source deep learning‐based air‐void detection algorithm for concrete microscopic images-Reference-Cited by-同舟云学术

Open‐source deep learning‐based air‐void detection algorithm for concrete microscopic images

Published:2022-03-23 Issue:2 Volume:286 Page:179-184
ISSN:0022-2720
Container-title:Journal of Microscopy
language:en
Short-container-title:Journal of Microscopy

Author:

Hilloulin B.¹,Bekrine I.¹,Schmitt E.²,Loukili A.¹

Affiliation:

1. Institut de Recherche en Génie Civil et Mécanique (GeM) UMR‐CNRS 6183, Ecole Centrale de Nantes Nantes France

2. Vicat L'Isle d'Abeau France

Publisher

Wiley

Subject

Histology,Pathology and Forensic Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jmi.13098

Reference19 articles.

1. The air requirement of frost resistant concrete;Powers T. C.;Highway Research Board Proceedings,1950

2. ASTM C457/C457M‐16(2016). Standard test method for microscopical determination of parameters of the air‐void system in hardened concrete.

3. Comité européen de Normalisation (CEN) EN 480‐11 (2005). Admixtures for concrete mortar and grout. test methods. Determination of air void characteristics in hardened concrete.

4. Determination of air-void parameters of hardened cement-based materials using X-ray computed tomography

5. Hardened Concrete Air Void Analysis with a Flatbed Scanner

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