3 papers
cs.CV2025
Harnessing Shared Relations via Multimodal Mixup Contrastive Learning for Multimodal Classification
Raja Kumar, Raghav Singhal, Pranamya Kulkarni +2
Deep multimodal learning has shown remarkable success by leveraging contrastive learning to capture explicit one-to-one relations across modalities. However, real-world data often…
eess.IV2025
Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models
Deval Mehta, Yiwen Jiang, Catherine L Jan +3
Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusi…
cs.CV2024
IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
Anurag Shandilya, Swapnil Bhat, Akshat Gautam +4
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-ta…