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A general approach to discovering, registering, and extracting features from raster maps.

, , , , , and . DRR, volume 7534 of SPIE Proceedings, page 753402. SPIE, (2010)

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Automatically and accurately conflating orthoimagery and street maps., , , , and . GIS, page 47-56. ACM, (2004)Building Linked Data from Historical Maps., , , , , , and . SemSci@ISWC, volume 2184 of CEUR Workshop Proceedings, page 59-67. CEUR-WS.org, (2018)Synthetic Map Generation to Provide Unlimited Training Data for Historical Map Text Detection., , , , and . GeoAI@SIGSPATIAL, page 17-26. ACM, (2021)DETECT: Deep Trajectory Clustering for Mobility-Behavior Analysis., , , , , and . IEEE BigData, page 988-997. IEEE, (2019)Kartta Labs: Collaborative Time Travel., , , , , , and . HICSS, page 1-10. ScholarSpace, (2021)Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine., and . ICPR (2), page 1034-1037. IEEE Computer Society, (2006)Kartta Labs: Unrendering Historical Maps., , , , , and . GeoAI@SIGSPATIAL, page 48-51. ACM, (2019)Towards the automated large-scale reconstruction of past road networks from historical maps., , , and . Comput. Environ. Urban Syst., (2022)Exploiting spatiotemporal patterns for accurate air quality forecasting using deep learning., , , , , , and . SIGSPATIAL/GIS, page 359-368. ACM, (2018)An Uncertainty Aware Method for Geographic Data Conflation., and . BigSpatial@SIGSPATIAL, page 20-27. ACM, (2018)