AI RESEARCH
DirPA: Addressing Prior Shift in Imbalanced Few-shot Crop-type Classification
arXiv CS.LG
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ArXi:2603.12905v1 Announce Type: new Real-world agricultural monitoring is often hampered by severe class imbalance and high label acquisition costs, resulting in significant data scarcity. In few-shot learning (FSL) -- a framework specifically designed for data-scarce settings