Classifying the Shapes of Buildings by Combining Distance Field Enhancement and a Convolution Neural Network
The shape classification of building objects is crucial in fields such as map generalization and spatial queries. Recently, convolutional neural networks (CNNs) have been used to capture high-level features and classify building shape patterns based on raster representations. However, this raster-ba...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/13/11/411 |
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