Building height estimation from street-view imagery using deep learning, image processing and automated geospatial analysis-Reference-Cited by-同舟云学术

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Building height estimation from street-view imagery using deep learning, image processing and automated geospatial analysis

Published:2023-11-11 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Al-Habashna Ala’a,Murdoch Ryan

Funder

Statistics Canada

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-17363-w.pdf

Reference43 articles.

1. Sampath A, Shan J (2010) Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds. IEEE Trans Geosci Remote Sens 48:1554–1567. https://doi.org/10.1109/TGRS.2009.2030180

2. Brunner D, Lemoine G, Bruzzone L, Greidanus H (2010) Building height retrieval from VHR SAR imagery based on an iterative simulation and matching technique. IEEE Trans Geosci Remote Sens 48:1487–1504. https://doi.org/10.1109/TGRS.2009.2031910

3. Google (2020) Street View Static API. https://developers.google.com/maps/documentation/streetview/intro. Accessed 1 Jul 2020

4. Mapillary (2014) Mapillary. https://www.mapillary.com/. Accessed 16 Jul 2020

5. Grab Holdings (2009) Open Street Cam. https://openstreetcam.org/map/@45.37744755572422,-75.65142697038783,18z. Accessed 1 Sep 2020

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