3 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.CV2026
A Calibrated Memorization Index (MI) for Detecting Training Data Leakage in Generative MRI Models
Yash Deo, Yan Jia, Toni Lassila +5
Image generative models are known to duplicate images from the training data as part of their outputs, which can lead to privacy concerns when used for medical image generation. We…
eess.IV2025★ 3 cited
Metrics that matter: Evaluating image quality metrics for medical image generation
Yash Deo, Yan Jia, Toni Lassila +5
Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for…
cs.CV2025★ 2 cited
Solving the long-tailed distribution problem by exploiting the synergies and balance of different techniques
Ziheng Wang, Toni Lassila, Sharib Ali
In real-world data, long-tailed data distribution is common, making it challenging for models trained on empirical risk minimisation to learn and classify tail classes effectively.…