Bilgisayar Mühendisliği Bölümü
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Task Offloading Methods in Fog-based IOT
(Fen Bilimleri Enstitüsü, 2024)Fog computing enables efficient task processing with low processing latency and bandwidth overhead between devices and the cloud in Internet of Things (IoT) networks. The reliability of these networks is critical as fog ... -
Süreç Madenciliğinde Tahmine Dayalı Süreç İzleme Tekniklerinin Kalitesinin Açıklanabilir Yapay Zeka Yöntemleri İle Değerlendirilmesi
(Fen Bilimleri Enstitüsü, 2024)Predictive process monitoring (PPM) techniques used in process mining aim to predict future attributes of a process, such as process outcome, next activity to be executed, or remaining work time. Many existing PPM approaches ... -
Evaluating Zero-Shot Learning Capabilities of Vision-Language Models
(Fen Bilimleri Enstitüsü, 2024)Vision-Language Models (VLMs) stand at the forefront of artificial intelligence research, aiming to bridge the gap between visual content and natural language understanding. Their significance lies in their potential to ... -
Predicting Disease-Gene Associations Via Machine Learning
(Bilişim Enstitüsü, 2024)In the quest to elucidate disease etiology and develop advanced diagnostic and treatment tools, knowing disease-gene relationships is of great importance. Traditional approaches based on manual curation fall short due ... -
Automatic Arrhythmia Classification from Electrocardiogram Measurements with Deep Learning
(Fen Bilimleri Enstitüsü, 2024)ECG signals have an important place in detecting arrhythmias. Arrhythmias are irregular heartbeats. One of the most popular studies in this field is the classification of arrhythmias with artificial neural networks. In the ... -
Agile Fight in Dynamic Environments: Bridging Reinforcement and Imitation Learning
(Fen Bilimleri Enstitüsü, 2024-06)In recent years, the utilization of drones has seen a remarkable increase across various sectors, including surveillance, delivery services, and environmental monitoring. This surge is largely attributed to advancements ... -
Curriculum Learning for Robot Navigation in Dynamic Environments with Uncertainties
(Fen Bilimleri Enstitüsü, 2024)In our study we wanted to see if there is any way we can make the training process of a DRL agent much easier, and optimize the success rate in the given tasks. In order to increase the speed of convergence we adopted ... -
A Fault-Tolerant Deployment Approach for Microservices in the Design Phase of Software Development Life Cycle
(Fen Bilimleri Enstitüsü, 2024-05-15)The concept of microservices architecture has gained significant interest in recent years, primarily due to its capacity to develop large-scale and extensive software systems while offering improved scalability, flexibility, ... -
Learning to Reconstruct Intensıty Images From Events
(Fen Bilimleri Enstitüsü, 2024)The past decade has seen significant progress in computer vision, leading to diverse applications across various domains. However, today’s artificial vision systems remain in their infancy compared to their biological ... -
Audio Classification with Few-Shot Learning
(Fen Bilimleri Enstitüsü, 2024-09-24)This thesis does a full experimental study of the few-shot classification problem in the audio domain to compare how well episodic and non-episodic training methods work.Three different optimization algorithms are trained ... -
A New Blockchain-Based PKI and A Digital Signature Format For Long-Term Validation of Digital Signatures
(Fen Bilimleri Enstitüsü, 2024-01-01)Traditional Public Key Infrastructure (PKI) has long been grappling with security issues arising from its centralized and non-transparent design. Despite Google's implementation of the Certificate Transparency (CT) project ... -
Histopatolojik Görüntülerde Bez Bölütleme için Çoklu Görev Öğrenimi
(Fen Bilimleri Enstitüsü, 2024-12-08)Analysis of histopathological images plays a crucial role in cancer detection and grading. Although well-trained pathologists can perform these tasks, the process is time-consuming and prone to errors. The advancement of ... -
Audio-Visual Emotion Recognition Using Deep Operational Networks
(Fen Bilimleri Enstitüsü, 2024)Emotions have a significant impact on interpersonal communication, marketing, healthcare, and the service sector. Consequently, much study continues to be conducted on the categorization of emotions up to the present day. ... -
Defending Against Distillation-Based Model Stealing Attacks
(Fen Bilimleri Enstitüsü, 2024)Knowledge Distillation (KD) allows a complex teacher network to pass on its skills to a simpler student network, improving the student's accuracy. However, KD can also be used in model theft, where adversaries try to copy ... -
Advancing Software Defect Prediction through Ensemble XAI Methods: Insights and Performance Evaluation
(Fen Bilimleri Enstitüsü, 2024-05)This doctoral thesis presents a comprehensive investigation into enhancing the interpretability and transparency of Machine Learning (ML) models in the domain of Software Defect Prediction (SDP) through Model-Agnostic ... -
Prediction of Drug Response in Cancer Using Hybrid Deep Neural Networks
(Fen Bilimleri Enstitüsü, 2024)Assessing the best treatment option for each patient is the main goal of precision medicine. Patients with the same diagnosis may display varying sensitivity to the applied treatment due to genetic heterogeneity, especially ... -
Detection of Phishing Web Pages by Combining Semantical and Visual Information
(Fen Bilimleri Enstitüsü, 2024-04-17)The increased frequency and sophistication of cybercrimes resulted in severe monetary loss for individuals and entities, increasing the demand for robust and sustainable solutions. Although there are countless anti-phishing ... -
Genetic Algorithm and Binary Masks For Co-Learning Multiple Datasets in Deep Neural Networks
(Fen Bilimleri Enstitüsü, 2024-01)This study addresses the challenges of 'catastrophic forgetting' and 'multi-task learning' encountered in the field of data classification and analysis, particularly with the use of Convolutional Neural Networks (CNNs). ... -
Otonom Oyun Ajanlarının Performansını Sürekli İyileştirmek için Görev Tabanlı Görsel Dikkat Kullanımı
(Fen Bilimleri Enstitüsü, 2024-01-05)Recent developments in the field of machine learning have led to the widespread acceptance of Deep Reinforcement Learning (DRL) techniques, which are a subset of machine learning, in the realm of digital intelligence. DRL ... -
Spatio-Temporal Isolation-Based Online Anomalous Trajectory Detection
(Fen Bilimleri Enstitüsü, 2024)The ubiquity of GPS data from taxis has spurred research in spatio-temporal trajectory analysis. Anomaly detection within these trajectories is vital for ensuring safety and efficiency. Existing methods address this by ...
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