3 papers indexed
Bas Meuwissen, Vasileios Tsouvalas, Nirvana Meratnia
Distributed Fine-Tuning (DFT) of large-scale Foundation Models (FMs) on resource-constrained edge devices is limited by local compute constraints and communication overhead. Parallel Split Learning (PSL) reduces client-side computation by keeping few model layers on each client a…
Gizem Karagoz, Tanir Ozcelebi, Nirvana Meratnia
In this study, a structured and methodological evaluation approach for eXplainable Artificial Intelligence (XAI) methods in medical image classification is proposed and implemented using LIME and SHAP explanations for chest X-ray interpretations. The evaluation framework integrat…
(Freddie) Liu, Gizem Karagoz, Nirvana Meratnia
Deep learning models are widely used for medical image analysis and require large datasets, while sufficient high-quality medical data for training are scarce. Data augmentation has been used to improve the performance of these models. The lack of transparency of complex deep-lea…