Applied Federated Model Personalization in the Industrial Domain
You can find below our recently published journal article in IEEE Open Journal of the Communications Society, entitled “Applied Federated Model Personalization in the Industrial Domain: A Comparative Study” and authored by I. Siniosoglou, V. Argyriou, G. Fragulis, P. Fouliras, G. Th. Papadopoulos, A. Lytos and P. Sarigiannidis. The study proposes an advanced Federated Learning […]
New paper
You can find below our recently accepted work in IEEE Access, entitled “Multimodal Explainable Artificial Intelligence: A Comprehensive Review of Methodological Advances and Future Research Directions” and authored by N. Rodis, C. Sardianos, P. Radoglou-Grammatikis, P. Sarigiannidis, I. Varlamis and Georgios Th. Papadopoulos. The current study focuses on systematically analyzing the recent advances in the […]
New paper
You can find below our recently accepted work at IEEE Access regarding “Distributed Maze Exploration Using Multiple Agents and Optimal Goal Assignment”, authored by M. Linardakis, I. Varlamis and G. Th. Papadopoulos. Many existing approaches to robotic exploration adopt optimization techniques through the development of multi-agent systems; however, such methods often overlook critical real-world factors, […]
Advances in Diffusion Models for Image Data Augmentation
You can find below (in arXiv format) our recent work on “Advances in Diffusion Models for Image Data Augmentation: A Review of Methods, Models, Evaluation Metrics and Future Research Directions”, authored by P. Alimisis, I. Mademlis, P. Radoglou-Grammatikis, P. Sarigiannidis and G. Th. Papadopoulos. Image data augmentation constitutes a critical methodology in modern computer vision […]
Neural natural language processing for long texts
You can find below our recently published work on “Neural natural language processing for long texts: A survey on classification and summarization”, accepted for publication at Elsevier Engineering Applications of Artificial Intelligence. The work comprises an introductory exploration to document analysis using modern Deep Neural Networks, addressing the primary challenges, concerns and existing solutions, while […]
