1 citations · 2 across the 7 of their papers we have counts for
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Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation
Naeem Paeedeh, Mahardhika Pratama, Wolfgang Mayer +3
Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem in the case of data scarcity.…
Cross-Domain Few-Shot Learning for Hyperspectral Image Classification Based on Mixup Foundation Model
Naeem Paeedeh, Mahardhika Pratama, Ary Shiddiqi +3
Although cross-domain few-shot learning (CDFSL) for hyper-spectral image (HSI) classification has attracted significant research interest, existing works often rely on an unrealist…
Cross-Domain Few-Shot Learning with Coalescent Projections and Latent Space Reservation
Naeem Paeedeh, Mahardhika Pratama, Imam Mustafa Kamal +3
Despite the progress in cross-domain few-shot learning, a model pre-trained with DINO combined with a prototypical classifier outperforms the latest SOTA methods. A crucial limitat…