65 citations · 160 across the 35 of their papers we have counts for
3 papers · 1 filter
Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision
Mélanie Gaillochet, Christian Desrosiers, Hervé Lombaert
Foundation models such as the recently introduced Segment Anything Model (SAM) have achieved remarkable results in image segmentation tasks. However, these models typically require…
Sparse Bayesian Networks: Efficient Uncertainty Quantification in Medical Image Analysis
Zeinab Abboud, Herve Lombaert, Samuel Kadoury
Efficiently quantifying predictive uncertainty in medical images remains a challenge. While Bayesian neural networks (BNN) offer predictive uncertainty, they require substantial co…
Neighbor-Aware Calibration of Segmentation Networks with Penalty-Based Constraints
Balamurali Murugesan, Sukesh Adiga Vasudeva, Bingyuan Liu +3
Ensuring reliable confidence scores from deep neural networks is of paramount significance in critical decision-making systems, particularly in real-world domains such as healthcar…