SOURCE-LINKED INTELLIGENCE
EndoFSA: Endoscopic Few-Shot Image Generation via Rank-Constrained Parameter Adaptation
WCE produces large-scale gastrointestinal image data yet pathological findings remain significantly underrepresented limiting the generalization performance of deep-learning based abnormality detection systems. SDG methods offer a practical solution to mitigate this imbalance. However their training directly on scarce abnormal samples often results in instability overfitting and structural distortions. Addressing these challenges requires controlled adaptation mechanisms that preserve anatomical priors while enabling realistic pathological variation. This paper presents EndoFSA a GAN-based mod
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T14:59:29.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.