Mapping mountain glaciers using an improved U-Net model with cSE-Reference-Cited by-同舟云学术

Mapping mountain glaciers using an improved U-Net model with cSE

Published:2022-02-22 Issue:1 Volume:15 Page:463-477
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Tian Suzheng¹,Dong Yusen¹,Feng Ruyi¹,Liang Dong²³⁴^ORCID,Wang Lizhe¹

Affiliation:

1. School of Computer Science, China University of Geosciences, Wuhan, People’s Republic of China

2. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of China

3. University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, People’s Republic of China

4. International Research Center of Big Data for Sustainable Development Goals, Beijing, People’s Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2022.2036834

Reference43 articles.

1. An ensemble architecture of deep convolutional Segnet and Unet networks for building semantic segmentation from high-resolution aerial images

2. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

3. Automated Extraction of Antarctic Glacier and Ice Shelf Fronts from Sentinel-1 Imagery Using Deep Learning

4. Terrain analysis and data modeling for alpine glacier mapping

5. Landsat-based inventory of glaciers in western Canada, 1985–2005

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