A Simplified Convolutional Network for Soil Pore Identification Based on Computed Tomography Imagery-Reference-Cited by-同舟云学术

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A Simplified Convolutional Network for Soil Pore Identification Based on Computed Tomography Imagery

Published:2019-09 Issue:5 Volume:83 Page:1309-1318
ISSN:0361-5995
Container-title:Soil Science Society of America Journal
language:en
Short-container-title:Soil Sci. Soc. Am. J.

Author:

Han Qiaoling¹²³,Zhao Yandong¹²³,Liu Lei¹²³,Chen Yuhong⁴,Zhao Yue¹²³

Affiliation:

1. School of Technology Beijing Forestry Univ.; Beijing 100083 P.R. China

2. Beijing Lab. of Urban and Rural Ecological Environment Beijing Municipal Education Commission; Beijing 100083 P.R. China

3. Key Lab of State Forestry Administration for Forestry Equipment and Automation; Beijing 10083 P.R. China

4. School of Astronautics Harbin Institute of Technology; Harbin 150001 P.R. China

Funder

Fundamental Research Funds for the Central Universities

National Basic Research Program of China

Beijing Common Construction Project

National Natural Science Youth Foundation of China

Publisher

Wiley

Subject

Soil Science

Link

http://onlinelibrary.wiley.com/wol1/doi/10.2136/sssaj2019.04.0119/fullpdf

Reference30 articles.

1. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data;Baveye;Geoderma,2010

2. Emergent properties of microbial activity in heterogeneous soil microenvironments: Different research approaches are slowly converging, yet major challenges remain;Baveye;Front. Microbiol.,2018

3. Accounting for sub-resolution pores in models of water and solute transport in soils based on computed tomography images: Are we there yet?;Baveye;J. Hydrol.,2017

4. Phase segmentation of X-ray computer tomography rock images using machine learning techniques: An accuracy and performance study;Chauhan;Solid Earth,2016

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2. APFlowNet: An inter-layer interpolation approach for soil CT images based on CNN and bidirectional optical flow;Soil and Tillage Research;2024-05

3. A Novel Method Combining U-Net with LSTM for Three-Dimensional Soil Pore Segmentation Based on Computed Tomography Images;Applied Sciences;2024-04-16

4. Soil pore structure and its research methods: A review;Soil and Water Research;2024-02-15

5. Multifractal analysis on CT soil images: Fluctuation analysis versus mass distribution;Chaos, Solitons & Fractals;2023-11

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