The increasing adoption of machine learning (ML) and artificial intelligence (AI) in critical decision-making has intensified demands for explainability and transparency, particularly in high-risk domains such as finance. This dissertation investigates how exp…
Brain tumors are life-threatening conditions that require accurate and timely diagnosis. In clinical practice, diagnosis is commonly performed through Magnetic Resonance Imaging (MRI) analysis by medical experts, which is time-consuming and subject to variabil…
This thesis examines the cybersecurity and privacy implications of Explainable Artificial Intelligence (XAI) methods in selected Machine Learning (ML) models. The study focuses on whether post-hoc explainability methods can expose sensitive information from he…
With the increasing ubiquity of Artificial Intelligence (AI) in daily life and into more critical applications, explainability has been brought under the spotlight due to ethical, social, and legal concerns. Explainability is particularly important in applicat…
2000-luvun aikana tekoälysovellukset ovat saavuttaneet erinomaisen suorituskyvyn useissa eri tehtävissä. Suuret datajoukot, kasvava laskennallinen teho sekä yhä monimutkaisemmat koneoppimismallit ovat mahdollistaneet sen. Valitettavasti nämä monimutkaiset mall…
The growing complexity of Deep Learning models, particularly Convolutional Neural Networks (CNNs), presents a fundamental challenge in critical applications: the opacity of their decisionmaking processes. This thesis addresses this interpretability gap by prop…
Recent years have seen instability in the electricity market and increasing energy demands in the world. Reliable electricity consumption forecasting is a helpful tool for consumers and other stakeholders to manage energy consumption more efficiently. This the…
With the onset of artificial intelligence (AI), machine learning (ML) approaches have become increasingly embedded into the drug discovery pipeline with the aim of accelerating research and reducing cost. Exemplary applications include quantitative structure-p…
As the demand for energy-efficient Artificial Intelligence (AI) grows, Spiking Neural Networks (SNNs) have emerged as a leading neuromorphic alternative to traditional deep learning. However, the complex, non-linear temporal dynamics of SNNs often result in a…
Artificial intelligence (AI) has become deeply embedded in modern decision-making systems, driving advances across science, industry and society. Yet, as models grow in scale and complexity, they increasingly operate as opaque systems whose internal reasoning…
Artificial intelligence (AI) is being adopted in diverse fields, including medical diagnosis and scientific research, to assist with decision-making thanks to its ability to learn underlying patterns from large amounts of data. However, these advances present…
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.
