Superpixel-based automatic image recognition for landslide deformation areas-Reference-Cited by-同舟云学术

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Superpixel-based automatic image recognition for landslide deformation areas

Published:2019-09 Issue: Volume:259 Page:105166
ISSN:0013-7952
Container-title:Engineering Geology
language:en
Short-container-title:Engineering Geology

Author:

Yang Yang,Song Shuliang,Yue Fucai,He Wen,Shao Wei,Zhao Kui,Nie Wen^ORCID

Funder

National Natural Science Foundation of China

Nanchong School Science and Technology Strategic Cooperation Special Project

Sichuan Bureau of Surveying, Mapping and Geoinformation Science and Technology Plan Project

Publisher

Elsevier BV

Subject

Geology,Geotechnical Engineering and Engineering Geology

Reference33 articles.

1. SLIC superpixels compared to state-of-the-art superpixel methods;Achanta;IEEE T. Pattern Anal.,2012

2. The Gradenbach Observatory—monitoring deep-seated gravitational slope deformation by geodetic, hydrological, and seismological methods;Brückl;Landslides,2013

3. Unmanned aerial systems for photogrammetry and remote sensing: a review;Colomina;Isprs J. Photogr. Remote Sens.,2014

4. Learning and incorporating top-down cues in image segmentation;He;Eccv,2006

5. The Landslide Handbook – A Guide to Understanding Landslides;Highland,2008

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