Magnetic Resonance Imaging (MRI) is a vital non-invasive tool for high-resolution brain imaging, yet its long acquisition time frequently results in patient movement leading to motion artifacts, particularly among non-compliant patients like newborns. While De…
Transfer learning in Natural Language Processing (NLP) mirrors a fundamental human cognitive ability: applying prior knowledge to learn new skills efficiently. Rather than training models from scratch for every new task, domain, or language, transfer learning…
Medical image segmentation plays a critical role in clinical diagnosis and treatment planning; however, the performance of deep learning models typically depends on large quantities of pixel-wise annotated data, which are costly and time-consuming to obtain. T…
This thesis addresses the problem of traffic congestion, which arises from increased vehicular queuing when the packet transmission load in the network exceeds the available buffer capacity. This condition leads to slower travel speed and also delays in travel…
Marine ecosystem models such as Atlantis have valuable insight into multispecies interactions, spatial dynamics and fisheries management, but their high computational cost limits are rapid scenario analysis and real-time decision making. This study presented a…
Machine learning models deployed in consequential domains can become unfair toward protected subgroups as the data they receive drifts over time, yet the protected attributes needed to measure fairness directly are often unavailable at runtime due to privacy r…
Bladder cancer (BC) is the most prevalent malignancy of the urinary system and ranks as the tenth most common cancer worldwide. Recent data indicate a significant increase in incidence, with hundreds of thousands of new cases diagnosed annually. Based on GLOBO…
Bladder cancer (BC) is the most prevalent malignancy of the urinary system and ranks as the tenth most common cancer worldwide. Recent data indicate a significant increase in incidence, with hundreds of thousands of new cases diagnosed annually. Based on GLOBO…
Data visualization is essential for navigating the vast volume of data that defines our time, letting humans use perception to make sense of complex datasets. Yet creating visualizations requires mastery of specialized programming languages, producing a gap be…
Understanding the world through natural language is a fundamental challenge in computer vision, requiring models to bridge the gap between geometric representations and semantic understanding. While recent advances in deep learning have enabled impressive prog…
Large-scale pretraining has produced powerful deep learning representations, but real-world data rarely match the clean, uniform assumptions of standard transfer learning. This dissertation uses heterogeneous data to describe settings in which information diff…
In federated learning (FL), private data leakage through gradient inversion depends strongly on design choices and data properties. We study this risk under an honest-but-curious server threat model, with a focus on clinical tabular data from MIMIC-IV and comp…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
