This thesis investigates the implementation of image denoising using Neural Networks (NN) in conjunction with wavelet transform techniques. For the purpose of data simulation, images are intentionally corrupted with additive white Gaussian noise (AWGN) at vari…
The three-dimensional organization of the genome and the interactions between biomolecules are fundamental to understanding cellular function and disease. Recent advances in sequencing technologies and structural biology have generated unprecedented amounts of…
This master's thesis deals with the optimization of building heating control using machine learning methods. Traditional control systems often fail to efficiently respond to the thermal inertia of buildings and variable external influences. Model Predictive Co…
Federated Learning (FL) enables multiple parties to collaboratively train a shared model without exposing raw data. However, FL often suffers from degraded performance due to three core challenges: non-IID data distributions, residual privacy risks, and limite…
This thesis addresses two critical challenges in Federated Learning (FL): enhancing Byzantine robustness to thwart poisoning attacks and advancing privacy-preserving mechanisms to mitigate data leakage risks. To address the first challenge, we develop a robust…
This thesis investigates the role of deep learning, focusing on convolutional neural networks and encoder-decoder architectures, to enhance medical image segmentation, specifically for pneumothorax identification in chest X-ray images. Pneumothorax, a critical…
Machine learning (ML) techniques have evolved rapidly in recent years and have shown impressive capabilities in feature extraction, pattern recognition, and causal inference. There has been an increasing attention to applying ML to medical applications, such a…
The coronavirus disease 2019 (COVID-19) pandemic has already become a global threat. To fight against COVID-19, effective and fast screening methods are needed. This study focuses on leveraging deep learning techniques to automatically detect COVID‐19 pneumoni…
There are three work on signature matching for document analysis. In the first work, we propose a large-scale signature matching method based on locality sensitive hashing (LSH). Shape Context features are used to describe the structure of signatures. Two stag…
This thesis investigates two complementary axes for improving Large Language Models (LLMs): the architecture used during pretraining, and the reasoning behavior elicited during post-training. The first part of the thesis addresses well-documented optimization…
This thesis presents the mathematical framework underlying two central architectures in modern deep learning: the feedforward neural network and the transformer model. Beginning from first principles, the report introduces the perceptron model and builds towar…
The rapid growth of urban populations has put unprecedented pressure on transportation systems, causing widespread problems such as congestion, accidents, and environmental pollution. Accurate traffic prediction is therefore essential for building smart cities…
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.
