Automatic alignment of geographic features in contemporary vector data and historical maps-Reference-Cited by-同舟云学术

Automatic alignment of geographic features in contemporary vector data and historical maps

Published:2017-11-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery
language:
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Author:

Duan Weiwei¹,Chiang Yao-Yi¹,Knoblock Craig A.¹,Jain Vinil¹,Feldman Dan¹,Uhl Johannes H.²,Leyk Stefan²

Affiliation:

1. University of Southern California

2. University of Colorado

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3149808.3149816

Reference21 articles.

1. Interactive Road Extraction with Pixel Force Fields

2. Automatically Conflating Road Vector Data with Orthoimagery

3. Automatically and Accurately Conflating Raster Maps with Orthoimagery

4. Y-Y Chiang and C A Knoblock. 2011. Recognition of multi-oriented multi-sized and curved text. In ICDAR. IEEE 1399--1403. 10.1109/ICDAR.2011.281 Y-Y Chiang and C A Knoblock. 2011. Recognition of multi-oriented multi-sized and curved text. In ICDAR. IEEE 1399--1403. 10.1109/ICDAR.2011.281

5. Y-Y Chiang and C A Knoblock. 2013. A general approach for extracting road vector data from raster maps. IJDAR (2013) 1--27. 10.1007/s10032-011-0177-1 Y-Y Chiang and C A Knoblock. 2013. A general approach for extracting road vector data from raster maps. IJDAR (2013) 1--27. 10.1007/s10032-011-0177-1

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