Identifying the place without text annotations: an assembled neural network framework for content-based raster map retrieval with cartographical morphological pattern
Currently, a majority of maps originate from volunteered sources. These volunteered maps have been created with the raster data structure and failed to follow the professional mapping principles. As the primary map languages, text and symbol annotations might be incorrect, or even missing. This pose...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-07-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2025.2522146 |
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