5 citations · 6 across the 5 of their papers we have counts for
5 papers
Fed-ReMasker: Federated Tabular Imputation under Feature-Level Missingness
Ioannis Papathanail, Rooholla Poursoleymani, Lubnaa Abdur Rahman +1
Multi-center clinical studies and biomedical research collaborations increasingly seek to utilize data across centers to build models that generalize beyond any single center. This…
Introducing the Swiss Food Knowledge Graph: AI for Context-Aware Nutrition Recommendation
Lubnaa Abdur Rahman, Ioannis Papathanail, Stavroula Mougiakakou
AI has driven significant progress in the nutrition field, especially through multimedia-based automatic dietary assessment. However, existing automatic dietary assessment systems…
Benchmarking Post-Hoc Unknown-Category Detection in Food Recognition
Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato +1
Food recognition models often struggle to distinguish between seen and unseen samples, frequently misclassifying samples from unseen categories by assigning them an in-distribution…
A SAM based Tool for Semi-Automatic Food Annotation
Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato +1
The advancement of artificial intelligence (AI) in food and nutrition research is hindered by a critical bottleneck: the lack of annotated food data. Despite the rise of highly eff…
Food Recognition and Nutritional Apps
Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato +2
Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet. Such apps can monitor food intake as a digita…