Classification of Sand Using Deep Learning-Reference-Cited by-同舟云学术

Classification of Sand Using Deep Learning

Published:2023-11 Issue:11 Volume:149 Page:
ISSN:1090-0241
Container-title:Journal of Geotechnical and Geoenvironmental Engineering
language:en
Short-container-title:J. Geotech. Geoenviron. Eng.

Author:

Li Linzhu¹^ORCID,Iskander Magued²^ORCID

Affiliation:

1. Assistant Professor, Dept. of Civil Engineering & Construction, Bradley Univ., Peoria, IL 61625. ORCID:

2. Professor and Chair, Dept. of Civil & Urban Engineering, New York Univ., 6 Metrotech Center, Brooklyn, NY 11201 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Geotechnical Engineering and Engineering Geology,General Environmental Science

Link

https://ascelibrary.org/doi/pdf/10.1061/JGGEFK.GTENG-11503

Reference40 articles.

1. ASTM. 2017. Standard practice for classification of soils for engineering purposes (unified soil classification system). ASTM D2487. West Conshohocken, PA: ASTM.

2. Classification of soil aggregates: A novel approach based on deep learning

3. Volumetric Particle Size Distribution and Variable Granular Density Soils

4. Interpretation of convolutional neural networks for acid sulfate soil classification;Beucher A.;Front. Environ. Sci.,2022

5. Geological mapping using remote sensing data: A comparison of five machine learning algorithms, their response to variations in the spatial distribution of training data and the use of explicit spatial information

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2. Use of Machine Learning for Automated Classification of Sand Type;Transportation Research Record: Journal of the Transportation Research Board;2024-07-25

3. DIA for Classification of Soils Using Machine Learning and Computer Vision;Springer Series in Geomechanics and Geoengineering;2024

4. Conclusions and Recommendations;Springer Series in Geomechanics and Geoengineering;2024

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