Large-scale Building Height Estimation from Single VHR SAR image Using Fully Convolutional Network and GIS building footprints-Reference-Cited by-同舟云学术

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Large-scale Building Height Estimation from Single VHR SAR image Using Fully Convolutional Network and GIS building footprints

Published:2019-05 Issue: Volume: Page:
ISSN:
Container-title:2019 Joint Urban Remote Sensing Event (JURSE)
language:
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Author:

Sun Yao,Hua Yuansheng,Mou Lichao,Zhu Xiao Xiang

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8792945/8808932/08809037.pdf?arnumber=8809037

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. Pano2Geo: An efficient and robust building height estimation model using street-view panoramas;ISPRS Journal of Photogrammetry and Remote Sensing;2024-09

2. Urban Building Height Extraction from Gaofen-7 Stereo Satellite Images Enhanced by Contour Matching;Remote Sensing;2024-04-27

3. Four seasonal composite Sentinel-2 images for the large-scale estimation of the number of stories in each individual building;Remote Sensing of Environment;2024-03

4. Reconstruction of 3D Information of Buildings from Single-View Images Based on Shadow Information;ISPRS International Journal of Geo-Information;2024-02-20

5. LUMNet: Land Use Knowledge Guided Multiscale Network for Height Estimation From Single Remote Sensing Images;IEEE Geoscience and Remote Sensing Letters;2024

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