AI RESEARCH
Dual Contrastive Network for Few-Shot Remote Sensing Image Scene Classification
arXiv CS.CV
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ArXi:2603.23161v1 Announce Type: new Few-shot remote sensing image scene classification (FS-RSISC) aims at classifying remote sensing images with only a few labeled samples. The main challenges lie in small inter-class variances and large intra-class variances, which are the inherent property of remote sensing images. To address these challenges, we propose a transfer-based Dual Contrastive Network (DCN), which incorporates two auxiliary supervised contrastive learning branches during the