most citedLess is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification Performance

5 citations · 5 across the 1 of their papers we have counts for

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1 paper

eess.IV2024★ 5 cited

Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification Performance

Daniel Wolf, Tristan Payer, Catharina Silvia Lisson +4

Self-supervised pre-training of deep learning models with contrastive learning is a widely used technique in image analysis. Current findings indicate a strong potential for contra…