Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples-Reference-Cited by-同舟云学术

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Paw-Net: Stacking ensemble deep learning for segmenting scanning electron microscopy images of fine-grained shale samples

Published:2022-11 Issue: Volume:168 Page:105218
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Yin Binqian,Hu Qinhong,Zhu Yingying,Zhao Chen,Zhou Keren

Funder

American Association of Petroleum Geologists

Geological Society of America

Office of Nuclear Energy

U.S. Department of Energy

Nuclear Energy University Program

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Information Systems

Reference53 articles.

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2. Development of a 2D and 3D computational algorithm for discontinuity structural geometry identification by artificial intelligence based on image processing techniques;Azarafza;Bull. Eng. Geol. Environ.,2019

3. Spacing and block volume estimation in discontinuous rock masses using image processing technique: a case study;Azarafza;Environ. Earth Sci.,2021

4. Application of an image processing-based algorithm for river-side granular sediment gradation distribution analysis;Azarafza;Advances in materials Research,2021

5. Deep learning-based landslide susceptibility mapping;Azarafza;Sci. Rep.,2021

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