This thesis investigates how relational structure can be introduced into tabular datasets by constructing graphs from spatial features and applying graph neural networks (GNNs) to enhance predictive modelling. A modular tool, Enhancer, was developed to automat…
Metagenomics has transformed microbial research by analyzing environmental DNA without the need for culturing. Metagenomic binning focuses on clustering the DNA fragments obtained from these environments based on their shared characteristics, providing insight…
(English) Modern networks support critical applications with increasingly diverse, complex, and dynamic requirements. Ensuring their proper functioning is vital to maintaining the reliability and availability of these dependent services. Anomaly Detection (AD)…
Recent years have witnessed the burgeoning of services based on data represented by graphs, which leads to rapid increase in the amount and complexity of such graph data. Graph Neural Networks (GNNs) are specialized neural models designed to represent and proc…
Graphs are powerful tools for modeling complex relationships between entities, making them essential in various domains, such as social networks, citation networks, molecular graphs, and road networks. In recent years, Graph Neural Networks (GNNs) have gained…
The increasing popularity of Artificial Intelligence, notably Deep Learning, has prompted its application across diverse real-world scenarios. Graph Neural Networks, a type of Deep Learning model developed for graph-structured data, have gained significant pop…
To achieve a graph representation, most Graph Neural Networks (GNNs) follow two steps: first, each graph is decomposed into a number of subgraphs (which we call the recursion step), and then the collection of subgraphs is encoded by several iterative pooling s…
The main subject of this work are certain parameterized algorithms, known as Graph Neural Networks, which operate on graphs. Specifically, we analyze what functions on graphs these algorithms can compute, or in other words, we analyze their expressivity.
Pengenalan emosi pada suara merupakan tugas kompleks yang krusial untuk interaksi manusia-mesin. Penelitian ini mengimplementasikan dan mengevaluasi model Convolutional Recurrent Neural Network (CRNN) yang menggabungkan keunggulan Convolutional Neural Network…
The main theme of this study is the application of advanced artificial intelligence techniques, especially Convolutional Neural Networks (CNN), for early detection of breast cancer. With the increasing importance of automated medical image analysis, this study…
X-ray Phase-Contrast Imaging (PCI) has revolutionized imaging in biomedical and materials science by enhancing contrast for soft tissues and subtle structural details that are challenging to detect with conventional absorption-based methods. Speckle-Based Imag…
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.
