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Task Specific Pretraining with Noisy Labels for Remote sensing Image Segmentation
In this work, we propose to explore the under-exploited potential of noisy labels for segmentation task specific pretraining, and exam its robustness when confronted with mismatched categories and different decoders during fine-tuning.
Map Generation from Large Scale Incomplete and Inaccurate Data Labels
Accurately and globally mapping human infrastructure is an important and challenging task with applications in routing, regulation compliance monitoring, and natural disaster response management etc..
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