Automatic Segmentation of Sinkholes Using a Convolutional Neural Network-Reference-Cited by-同舟云学术

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Automatic Segmentation of Sinkholes Using a Convolutional Neural Network

Published:2022-02 Issue:2 Volume:9 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth and Space Science

Author:

Rafique Muhammad Usman¹^ORCID,Zhu Junfeng²³^ORCID,Jacobs Nathan⁴^ORCID

Affiliation:

1. Kitware Inc. Clifton Park NY USA

2. Kentucky Geological Survey University of Kentucky Lexington KY USA

3. Department of Earth and Environmental Sciences University of Kentucky Lexington KY USA

4. Department of Computer Science University of Kentucky Lexington KY USA

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EA002195

Reference36 articles.

1. Landscape Classification with Deep Neural Networks

2. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

3. Global distribution of carbonate rocks and karst water resources

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1. Detection and automatic identification of loess sinkholes from the perspective of LiDAR point clouds and deep learning algorithm;Geomorphology;2024-11

2. Detection of karst depression in Brazil comparing different semantic and instance segmentations and global digital elevation models;Geomorphology;2024-07

3. Deep-Learning-Based Automatic Sinkhole Recognition: Application to the Eastern Dead Sea;Remote Sensing;2024-06-21

4. Fracture characterization based on data fusion technology and its application in rockfall hazard assessment;Environmental Earth Sciences;2024-03-21

5. IDENTIFICAÇÃO DE DEPRESSÕES CÁRSTICAS POR MEIO DE MODELOS DIGITAIS DE ELEVAÇÃO NA PARTE OESTE DO GRUPO BAMBUÍ;Revista Brasileira de Geografia Física;2024-03-14

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