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Recent Submissions

Privacy-preserving federated machine learning on FAIR health data: A real-world application Sınacı, Ali Anıl; Gencturk, Mert; Alvarez-Romero, Celia; Laleci Erturkmen, Gokce Banu; Martinez-Garcia, Alicia; Escalona-Cuaresma, María José; Parra-Calderon, Carlos Luis (2024-12-01) Objective: This paper introduces a privacy-preserving federated machine learning (ML) architecture built upon Findable, Accessible, Interoperable, and Reusable (FAIR) health data. It aims to devise an architecture for exec...
Potential-based reward shaping using state–space segmentation for efficiency in reinforcement learning Bal, Melis İlayda; Aydın, Hüseyin; İyigün, Cem; Polat, Faruk (2024-08-01) Reinforcement Learning (RL) algorithms encounter slow learning in environments with sparse explicit reward structures due to the limited feedback available on the agent's behavior. This problem is exacerbated particularly ...
Field teams coordination for earthquake-damaged distribution system energization Işık, İlker; Aydın Göl, Ebru (2024-05-01) The re-energization of electrical distribution systems in a post-disaster scenario is of grave importance as most modern infrastructure systems rely heavily on the presence of electricity. This paper introduces a method to...
SegIns: A simple extension to instance discrimination task for better localization learning Baydar, Melih; Akbaş, Emre (2024-04-01) Recent self-supervised learning methods, where instance discrimination task is a fundamental way of pretraining convolutional neural networks (CNN), excel in transfer learning performance. Even though instance discriminati...
Targeted marketing on social media: utilizing text analysis to create personalized landing pages Çetinkaya, Yusuf Mucahit; Külah, Emre; Toroslu, İsmail Hakkı; Davulcu, Hasan (2024-04-01) The widespread use of social media has rendered it a critical arena for online marketing strategies. To optimize conversion rates, the landing pages must effectively respond to a visitor segment’s pain points that they nee...
GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening Ioannou, Iacovos; Nagaradjane, Prabagarane; Angın, Pelin; Balasubramanian, Palaniappan; Kavitha, Karthick Jeyagopal; Murugan, Palani; Vassiliou, Vasos (2024-03-01)
Early detection of fake news on emerging topics through weak supervision Akdag, Serhat Hakki; Çiçekli, Fehime Nihan (2024-01-01) In this paper, we present a methodology for the early detection of fake news on emerging topics through the innovative application of weak supervision. Traditional techniques for fake news detection often rely on fact-chec...
Evaluating the quality of visual explanations on chest X-ray images for thorax diseases classification Rahimiaghdam, Shakiba; Alemdar, Hande (2024-01-01) Deep learning models are extensively used but often lack transparency due to their complex internal mechanics. To bridge this gap, the field of explainable AI (XAI) strives to make these models more interpretable. However,...
Traffic signal optimization using multiobjective linear programming for oversaturated traffic conditions Coşkun, Mustafa Murat; Şener, Cevat; Toroslu, İsmail Hakkı (2024-01-01) In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions w...
A Compact Multi-Exposure File Format for Backward and Forward Compatible HDR Imaging Sekmen, Selin; Akyüz, Ahmet Oğuz (2024-01-01) High dynamic range (HDR) imaging techniques offer photographers the ability to capture the full range of luminance in real-world scenes, overcoming the limitations of capture and display devices. One popular method for cre...
A smart e-health framework for monitoring the health of the elderly and disabled Yazıcı, Adnan; Zhumabekova, Dana; Nurakhmetova, Aidana; Yergaliyev, Zhanggir; Yatbaz, Hakan Yekta; Makisheva, Zaida; Lewis, Michael; EVER, ENVER (2023-12-01) The healthcare sector is experiencing a significant transformation due to the widespread adoption of IoT-based systems, especially in the care of elderly and disabled individuals who can now be monitored through portable a...
A Novel Graph Neural Network for Zone-Level Urban-Scale Building Energy Use Estimation Halaçll, Eren Gökberk; Canll, Ilkim; Işeri, Orçun Koral; Yavuz, Feyza; Akgül, Çaǧla Meral; Kalkan, Sinan; Gürsel Dino, İpek (2023-11-15) Buildings are highly responsible for total energy consumption in cities; therefore, accurate estimation of building energy consumption is essential for developing energy-efficient strategies on an urban scale. Data-driven ...
Special issue on High-Performance Computing Conference (BASARIM 2022) Kaya, Kamer; Şener, Cevat; Yenigün, Hüsnü (2023-11-01) This is an editorial for the Special Issue on the 7th High-Performance Computing Conference (BAŞARIM 2022) organized on May 11–13, 2022, at Sabanci University Altunizade Digital Campus, İstanbul.
Wine in the Cloud, or: Smart Vineyards with a Distributed "Extreme Data Database" and Supercomputing Karagöz, Pınar; Harsh, Piyush; Hachinger, Stephan; Derquennes, Marc; Edmonds, Andy; Golasowski, Martin; Hayek, Mohamad; Martinovič, Jan (2023-10-25) In this contribution, we sketch an application of Earth System Sciences and Cloud-/Big-Data- based IT, which shall soon leverage European supercomputing facilities: smart viticulture, as put into practice by Terraview. Ter...
Devising a Uniform Description of Underground Built Heritage Sites Karagöz, Pınar (2023-09-01)
Analysis of Vector-Network-Analyzer-Based Power Sensor Calibration Method Application Danaci, Erkan; Bayrak, Yusuf; Çetinkaya, Anıl; Arslan, Murat; Sakarya, Handan; Dogan, Aliye Kartal; Tunay, Gulsun (2023-09-01) Radio Frequency (RF) power sensor calibration is one of the essential measurements in RF and microwave metrology. For a reliable and accurate power sensor calibration, there are various methods, such as the substitution me...
Solving an industry-inspired generalization of lifelong MAPF problem including multiple delivery locations Polat, Faruk (2023-08-01)
Correlation Loss: Enforcing Correlation between Classification and Localization Kahraman, Fehmi; Oksuz, Kemal; KALKAN, SİNAN; Akbaş, Emre (2023-06-27) Object detectors are conventionally trained by a weighted sum of classification and localization losses. Recent studies (e.g., predicting IoU with an auxiliary head, Generalized Focal Loss, Rank & Sort Loss) have shown tha...
Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detection Demirel, Berkan; Baran, Orhun Buğra; Cinbiş, Ramazan Gökberk (2023-06-21) Few-shot object detection, the problem of modelling novel object detection categories with few training instances, is an emerging topic in the area of few-shot learning and ob- ject detection. Contemporary techniques can b...
Effect of Context on Smartphone Users' Typing Performance in the Wild Akpinar, Elgin; YILMAZ, YELİZ; Karagöz, Pınar (2023-06-10) Smartphones play a crucial role in daily activities, however, situationally-induced impairments and disabilities (SIIDs) can easily be experienced depending on the context. Previous studies explored the effect of context b...

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