1 citations · 2 across the 3 of their papers we have counts for
5 papers · 1 filter
FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbation
Yan Luo, Muhammad Osama Khan, Congcong Wen +6
Recent progress in generative AI, especially diffusion models, has demonstrated significant utility in text-to-image synthesis. Particularly in healthcare, these models offer immen…
FairCLIP: Harnessing Fairness in Vision-Language Learning
Yan Luo, Min Shi, Muhammad Osama Khan +9
Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated i…
MeSa: Masked, Geometric, and Supervised Pre-training for Monocular Depth Estimation
Muhammad Osama Khan, Junbang Liang, Chun-Kai Wang +2
Pre-training has been an important ingredient in developing strong monocular depth estimation models in recent years. For instance, self-supervised learning (SSL) is particularly e…
FairVision: Equitable Deep Learning for Eye Disease Screening via Fair Identity Scaling
Yan Luo, Muhammad Osama Khan, Yu Tian +5
Equity in AI for healthcare is crucial due to its direct impact on human well-being. Despite advancements in 2D medical imaging fairness, the fairness of 3D models remains underexp…
Revisiting Fine-Tuning Strategies for Self-supervised Medical Imaging Analysis
Muhammad Osama Khan, Yi Fang
Despite the rapid progress in self-supervised learning (SSL), end-to-end fine-tuning still remains the dominant fine-tuning strategy for medical imaging analysis. However, it remai…