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Text-guided Foundation Model Adaptation for Pathological Image Classification
Yunkun Zhang, Jin Gao, Mu Zhou +4
The recent surge of foundation models in computer vision and natural language processing opens up perspectives in utilizing multi-modal clinical data to train large models with str…
Exploring Data Redundancy in Real-world Image Classification through Data Selection
Zhenyu Tang, Shaoting Zhang, Xiaosong Wang
Deep learning models often require large amounts of data for training, leading to increased costs. It is particularly challenging in medical imaging, i.e., gathering distributed da…
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Dequan Wang, Xiaosong Wang, Lilong Wang +12
Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enabl…