Filling gaps of cartographic polylines by using an encoder–decoder model
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DOI: 10.1080/13658816.2022.2055036
Abstract: Abstract Geospatial studies must address spatial data quality, especially in data-driven research. An essential concern is how to fill spatial data gaps (missing data), such as for cartographic polylines. Recent advances in deep learning have… read more here.
Keywords: filling gaps; polylines using; cartographic polylines; using encoder ... See more keywords