3 papers
cs.CV2025
Evaluating Multiple Instance Learning Strategies for Automated Sebocyte Droplet Counting
Maryam Adelipour, Gustavo Carneiro, Jeongkwon Kim
Sebocytes are lipid-secreting cells whose differentiation is marked by the accumulation of intracellular lipid droplets, making their quantification a key readout in sebocyte biolo…
cs.CV2025
Risk Estimation of Knee Osteoarthritis Progression via Predictive Multi-task Modelling from Efficient Diffusion Model using X-ray Images
David Butler, Adrian Hilton, Gustavo Carneiro
Medical imaging plays a crucial role in assessing knee osteoarthritis (OA) risk by enabling early detection and disease monitoring. Recent machine learning methods have improved ri…
cs.LG2025
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
Hanxuan Wang, Na Lu, Xueying Zhao +4
Learning from noisy labels (LNL) aims to train high-performance deep models using noisy datasets. Meta learning based label correction methods have demonstrated remarkable performa…