62 citations · 84 across the 14 of their papers we have counts for
5 papers · 1 filter
Applied Federated Model Personalisation in the Industrial Domain: A Comparative Study
Ilias Siniosoglou, Vasileios Argyriou, George Fragulis +4
The time-consuming nature of training and deploying complicated Machine and Deep Learning (DL) models for a variety of applications continues to pose significant challenges in the…
Advances in Diffusion Models for Image Data Augmentation: A Review of Methods, Models, Evaluation Metrics and Future Research Directions
Panagiotis Alimisis, Ioannis Mademlis, Panagiotis Radoglou-Grammatikis +2
Image data augmentation constitutes a critical methodology in modern computer vision tasks, since it can facilitate towards enhancing the diversity and quality of training datasets…
CEASEFIRE: An AI-powered system for combatting illicit firearms trafficking
Jorgen Cani, Ioannis Mademlis, Marina Mancuso +19
Modern technologies have led illicit firearms trafficking to partially merge with cybercrime, while simultaneously permitting its off-line aspects to become more sophisticated. Law…
StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
Pavlos S. Bouzinis, Panagiotis Radoglou-Grammatikis, Ioannis Makris +5
Federated learning (FL) is a decentralized learning technique that enables participating devices to collaboratively build a shared Machine Leaning (ML) or Deep Learning (DL) model…
Illicit object detection in X-ray images using Vision Transformers
Jorgen Cani, Ioannis Mademlis, Adamantia Anna Rebolledo Chrysochoou +1
Illicit object detection is a critical task performed at various high-security locations, including airports, train stations, subways, and ports. The continuous and tedious work of…