Deep Learning-Based Segmentation for Field Evaluation of Riprap and Large-Sized Aggregates-Reference-Cited by-同舟云学术

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Deep Learning-Based Segmentation for Field Evaluation of Riprap and Large-Sized Aggregates

Published:2023-03-23 Issue: Volume: Page:
ISSN:
Container-title:Geo-Congress 2023
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Author:

Luo Jiayi¹¹¹²³,Huang Haohang¹¹¹²³,Qamhia Issam I. A.¹¹¹²³,Hart John M.¹¹¹²³,Tutumluer Erol¹¹¹²³

Affiliation:

1. Newmark Civil Engineering Laboratory, Univ. of Illinois at Urbana-Champaign, Urbana, IL

2. Computer Vision and Robotics Laboratory, Univ. of Illinois at Urbana-Champaign, Urbana, IL

3. Newmark Civil Engineering Laboratory, Univ. of Illinois at Urbana-Champaign, Urbana, IL.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484678.043

Reference17 articles.

1. The effects of aggregate characteristics on the performance of Portland cement concrete;Fowler D. W.;International Centre for Aggregate Research, ICAR,2003

2. Investigation of aggregate properties influencing railroad ballast performance;Wnek M. A.;Transportation research record,2013

3. Aggregate Morphology Affecting Strength and Permanent Deformation Behavior of Unbound Aggregate Materials

4. Lagasse, P. F. (2006). Riprap design criteria, recommended specifications, and quality control (Vol. 568). Transportation Research Board.

5. The shape of rock particles, a critical review

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