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Yu et al., 2022 - Google Patents

Filling gaps of cartographic polylines by using an encoder–decoder model

Yu et al., 2022

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Document ID
15643510628915638105
Author
Yu W
Chen Y
Publication year
Publication venue
International Journal of Geographical Information Science

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Snippet

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 shown promise in filling holes in images …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

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    • G06F17/21—Text processing
    • G06F17/24—Editing, e.g. insert/delete
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20—Handling natural language data
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    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/206—Drawing of charts or graphs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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    • G06—COMPUTING; CALCULATING; COUNTING
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