51 citations · 72 across the 23 of their papers we have counts for
24 papers
Label-Free Concept Drift Assessment for Reliable AI in Emerging Wireless Applications
Athanasios Tziouvaras, Carolina Fortuna, George Floros +4
Machine learning models deployed in non-stationary environments degrade silently, since as the input distribution drifts their accuracy decays without an error signal and without l…
A Representation Learning Approach to Feature Drift Detection in Wireless Networks
Athanasios Tziouvaras, Blaz Bertalanic, George Floros +3
AI is foreseen to be a centerpiece in next generation wireless networks enabling enabling ubiquitous communication as well as new services. However, in real deployment, feature dis…
Malware Detection in Docker Containers: An Image is Worth a Thousand Logs
Akis Nousias, Efklidis Katsaros, Evangelos Syrmos +7
Malware detection is increasingly challenged by evolving techniques like obfuscation and polymorphism, limiting the effectiveness of traditional methods. Meanwhile, the widespread…
State of play and future directions in industrial computer vision AI standards
Artemis Stefanidou, Panagiotis Radoglou-Grammatikis, Vasileios Argyriou +3
The recent tremendous advancements in the areas of Artificial Intelligence (AI) and Deep Learning (DL) have also resulted into corresponding remarkable progress in the field of Com…
Federated Detection of Open Charge Point Protocol 1.6 Cyberattacks
Christos Dalamagkas, Panagiotis Radoglou-Grammatikis, Pavlos Bouzinis +7
The ongoing electrification of the transportation sector requires the deployment of multiple Electric Vehicle (EV) charging stations across multiple locations. However, the EV char…
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…
A Closer Look at Data Augmentation Strategies for Finetuning-Based Low/Few-Shot Object Detection
Vladislav Li, Georgios Tsoumplekas, Ilias Siniosoglou +4
Current methods for low- and few-shot object detection have primarily focused on enhancing model performance for detecting objects. One common approach to achieve this is by combin…
Leveraging Digital Twin Technologies for Public Space Protection and Vulnerability Assessment
Artemis Stefanidou, Jorgen Cani, Thomas Papadopoulos +4
Over the recent years, the protection of the so-called `soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has em…
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…
CloudCap (C2app) : A Cloud-Based Platform for Packet Analysis On The Edge
Kyriazis Kokkinos, Ioannis Polymenidis, Ilias Siniosoglou +2
Data exchange through mobile devices is rapidly increasing due to the high information demands of today's applications. The need for monitoring the exchanged traffic becomes import…
Enhancing Performance for Highly Imbalanced Medical Data via Data Regularization in a Federated Learning Setting
Georgios Tsoumplekas, Ilias Siniosoglou, Vasileios Argyriou +2
The increased availability of medical data has significantly impacted healthcare by enabling the application of machine / deep learning approaches in various instances. However, me…
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…
Autonomous AI-enabled Industrial Sorting Pipeline for Advanced Textile Recycling
Yannis Spyridis, Vasileios Argyriou, Antonios Sarigiannidis +2
The escalating volumes of textile waste globally necessitate innovative waste management solutions to mitigate the environmental impact and promote sustainability in the fashion in…
Evaluating the Efficacy of AI Techniques in Textual Anonymization: A Comparative Study
Dimitris Asimopoulos, Ilias Siniosoglou, Vasileios Argyriou +5
In the digital era, with escalating privacy concerns, it's imperative to devise robust strategies that protect private data while maintaining the intrinsic value of textual informa…
Benchmarking Advanced Text Anonymisation Methods: A Comparative Study on Novel and Traditional Approaches
Dimitris Asimopoulos, Ilias Siniosoglou, Vasileios Argyriou +6
In the realm of data privacy, the ability to effectively anonymise text is paramount. With the proliferation of deep learning and, in particular, transformer architectures, there i…
Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings
Georgios Tsoumplekas, Vladislav Li, Ilias Siniosoglou +5
In the ever-evolving era of Artificial Intelligence (AI), model performance has constituted a key metric driving innovation, leading to an exponential growth in model size and comp…
A Complete Survey on Contemporary Methods, Emerging Paradigms and Hybrid Approaches for Few-Shot Learning
Georgios Tsoumplekas, Vladislav Li, Panagiotis Sarigiannidis +1
Despite the widespread success of deep learning, its intense requirements for vast amounts of data and extensive training make it impractical for various real-world applications wh…
Evaluation of AI-Supported Input Methods in Augmented Reality Environment
Akos Nagy, Thomas Lagkas, Panagiotis Sarigiannidis +1
Augmented Reality (AR) solutions are providing tools that could improve applications in the medical and industrial fields. Augmentation can provide additional information in traini…
AI-Powered Interfaces for Extended Reality to support Remote Maintenance
Akos Nagy, George Amponis, Konstantinos Kyranou +4
High-end components that conduct complicated tasks automatically are a part of modern industrial systems. However, in order for these parts to function at the desired level, they n…
Evaluation of Environmental Conditions on Object Detection using Oriented Bounding Boxes for AR Applications
Vladislav Li, Barbara Villarini, Jean-Christophe Nebel +3
The objective of augmented reality (AR) is to add digital content to natural images and videos to create an interactive experience between the user and the environment. Scene analy…
The evolution of argumentation mining: From models to social media and emerging tools
Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis +1
Argumentation mining is a rising subject in the computational linguistics domain focusing on extracting structured arguments from natural text, often from unstructured or noisy tex…
Smart IoT Cameras for Crowd Analysis based on augmentation for automatic pedestrian detection, simulation and annotation
Antoine Rimboux, Rob Dupre, Thomas Lagkas +3
Smart video sensors for applications related to surveillance and security are IOT-based as they use Internet for various purposes. Such applications include crowd behaviour monitor…
Argumentation Mining: Exploiting Multiple Sources and Background Knowledge
Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis +1
The field of Argumentation Mining has arisen from the need of determining the underlying causes from an expressed opinion and the urgency to develop the established fields of Opini…
A Multilayer Comparative Study of XG-PON and 10G-EPON Standards
Charalampos Konstadinidis, Panagiotis Sarigiannidis, Periklis Chatzimisios +2
The purpose of this paper is to provide a multilayer review of the two major standards in next generation Passive Optical Networks (PONs) and technologies, the ITU-T 10-Gigabit-cap…