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eess.IV2024
IMIL: Interactive Medical Image Learning Framework
Adrit Rao, Andrea Fisher, Ken Chang +4
Data augmentations are widely used in training medical image deep learning models to increase the diversity and size of sparse datasets. However, commonly used augmentation techniq…
cs.CV2024
Concept Weaver: Enabling Multi-Concept Fusion in Text-to-Image Models
Gihyun Kwon, Simon Jenni, Dingzeyu Li +3
While there has been significant progress in customizing text-to-image generation models, generating images that combine multiple personalized concepts remains challenging. In this…