Research map / Detection and segmentation / Open-set and few-shot detection
PARCS: A Deployment-Oriented AI System for Robust Parcel-Level Cropland Segmentation of Satellite Images
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add active-learning rounds with additional pixel annotations (ablation) | PARCS · In-house dataset | mIoU: 37.81 -> 65.16 | Helped |
| replace parcel region extraction with Felzenszwalb-Huttenlocher superpixels (ablation) | PARCS · In-house dataset | mIoU: 65.16 -> 45.32 | Hurt |
| replace parcel region extraction with SNIC superpixels (ablation) | PARCS · In-house dataset | mIoU: 65.16 -> 50.29 | Hurt |
| train with limited pixel labels instead of parcel-level annotations | PARCS · PASTIS (5-fold cross-validation) | mIoU: 63.1 -> 61.7 | Mixed |
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