In today’s data-driven world, machine learning (ML) powers critical decisions across sectors such as healthcare and finance, but the opacity of complex “black-box” models undermines trust, accountability, and adoption. This thesis tackles the urgent challenge…
Machine learning is no longer limited to low-risk tasks, but it is also being used in critical decision-making systems. Consequently, machine learning has a direct effect on individuals' lives in domains such as recidivism prediction (COMPAS) and loan approval…
Machine learning quantique appliqué à des cas d'usage industriels Cette thèse explore le développement de méthodes en Apprentissage Automatique Quantique (Quantum Machine Learning, QML) destinées aux applications industrielles, en mettant l'accent sur la jonct…
The adoption of network virtualization and cloud computing has introduced new complexities and attack vectors, which demands more intelligent and scalable security solutions. In such cases, traditional Intrusion Detection Systems (IDS) often have struggle to p…
The increasing reliance on Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) systems has raised critical concerns regarding their vulnerability to cyberattacks. While machine learning (ML) methods have emerged as effective t…
With the complexity of the cyber threats, the issue of developing more intelligent and flexible systems that can detect the known and unknown intrusions in real-time has become a burning matter. The paper suggests a hybrid threat detection scheme that combines…
The growing connectivity of Industrial Control Systems (ICS) has increased their exposure to cyber threats, posing serious risks to both critical infrastructure (e.g., power plants, water systems) and industrial operations. Although Machine Learning (ML)-based…
Federated Learning (FL) has emerged as a significant tool in healthcare machine learning, enabling institutions to collaboratively train models while maintaining data privacy. This dissertation describes the implementation of a real-world healthcare FL project…
This thesis presents a comprehensive study on angle of arrival (AoA) estimation techniques for spectrum sharing in next-generation (NextG) wireless communication systems. The investigation encompasses signal processing methods, including multiple signal classi…
Geleneksel makine öğrenmesi (GMÖ) ve derin öğrenme (DÖ), yapay zeka alanında iki önemli yaklaşımdır. GMÖ, tahmine dayalı modeller oluşturmak için destek vektör makineleri (DVM), k-en yakın komşular, karar ağaçları gibi çeşitli algoritmalar kullanır. Bu yaklaşı…
According to a study performed by John Hopkins Medicine in 2023, misdiagnoses make up approximately 11.1% of total diagnoses in the United States, which result in anything from minor to fatal error for the patient. One of the main contributors to this unfortun…
Recently the use of resource-constrained edge devices to perform machine learning tasks has gained substantial research attention. The need to perform such tasks arises from the vast amounts of sensors, and IoT and smart devices that generate large swaths of d…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
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قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
