A review of recent advances in scanned topographic map processing-Reference-Cited by-同舟云学术

A review of recent advances in scanned topographic map processing

Published:2019-02 Issue: Volume:328 Page:75-87
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Liu Tiange,Xu Pengfei,Zhang Shihui

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference105 articles.

1. A survey of digital map processing techniques;Chiang;ACM Comput. Surv.,2014

2. Government of Canada. National Topographic System Maps. Earth Sciences – Geography. Natural Resources Canada. Retrieved August 11, 2016. (http://www.nrcan.gc.ca/earth-sciences/geography/topographic-information/maps/9767).

3. Analysis of historic landscape patterns with a geographical information system – a methodological outline;Kienast;Landsc. Ecol,1993

4. Impact of data integration technique on historical land-use/land-cover change: comparing historical maps with remote sensing data in the Belgian Ardennes;Petit;Landsc. Ecol.,2002

5. Forest cover changes in the northern Carpathians in the 20th century: a slow transition;Jacek;J. Land Use Sci.,2007

Cited by 23 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. Automatic Detection and 3D Reconstruction of Buildings from Historical Maps;Applied Artificial Intelligence;2024-07-24

2. Assessing spatially explicit long-term landscape dynamics based on automated production of land category layers from Danish late 19th century topographic maps;2024-04-19

3. Assessing long-term landscape dynamics based on automated production of land category layers from Danish late 19th century topographic maps;2024-03-11

4. Unleashing the power of old maps: Extracting symbology from nineteenth century maps using convolutional neural networks to quantify modern land use on historic wetlands;Ecological Indicators;2024-01

5. Exploiting Polygon Metadata to Understand Raster Maps - Accurate Polygonal Feature Extraction;Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems;2023-11-13