Convolution neural network based on fusion parallel multiscale features for segmenting fractures in coal-rock images-Reference-Cited by-同舟云学术

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Convolution neural network based on fusion parallel multiscale features for segmenting fractures in coal-rock images

Published:2020-03-13 Issue:02 Volume:29 Page:1
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:
Short-container-title:J. Electron. Imag.

Author:

Lu Fengli¹,Fu Chengcai¹,Zhang Guoying¹,Zhang Wei¹,Xie Yajun¹,Li Zhiwei¹

Affiliation:

1. China University of Mining and Technology, Beijing

Funder

National Natural Science Foundation of China

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An alternative rotating object detection method for rock particle size distribution analysis;Powder Technology;2024-08

2. Utilizing semantic-level computer vision for fracture trace characterization of hard rock pillars in underground space;Geoscience Frontiers;2024-03

3. Evolution of Coal Microfracture by Cyclic Fracturing of Liquid Nitrogen Based on μCT and Convolutional Neural Networks;Rock Mechanics and Rock Engineering;2023-12-13

4. A review of deep leaning in image classification for mineral exploration;Minerals Engineering;2023-12

5. Deep learning in image segmentation for mineral production: A review;Computers & Geosciences;2023-11

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