Self-Filtered Learning for Semantic Segmentation of Buildings in Remote Sensing Imagery With Noisy Labels
Not all building labels for training improve the performance of the deep learning model. Some labels can be falsely labeled or too ambiguous to represent their ground truths, resulting in poor performance of the model. For example, building labels in OpenStreetMap (OSM) and Microsoft Building Footpr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9992041/ |