7 citations · 13 across the 22 of their papers we have counts for
25 papers
Facial Affect Analysis for Service-Oriented Systems: Advances, Challenges, and Future Visions
Spyridon Georgiou, Aggelos Psiris, Thomas Lagkas +4
Facial Affect Analysis (FAA) is evolving from a stand-alone recognition task into a reusable perception capability for Service-Oriented Software Ecosystems (SoSE). This paper prese…
Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions
Aggelos Psiris, Vasileios Argyriou, Evangelos K. Markakis +5
Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towards adaptive, multi-function…
FR-GESTURE: An RGBD Dataset For Gesture-based Human-Robot Interaction In First Responder Operations
Konstantinos Foteinos, Georgios Angelidis, Aggelos Psiris +3
The ever increasing intensity and number of disasters make even more difficult the work of First Responders (FRs). Artificial intelligence and robotics solutions could facilitate t…
Interactive Augmented Reality-enabled Outdoor Scene Visualization For Enhanced Real-time Disaster Response
Dimitrios Apostolakis, Georgios Angelidis, Vasileios Argyriou +2
A user-centered AR interface for disaster response is presented in this work that uses 3D Gaussian Splatting (3DGS) to visualize detailed scene reconstructions, while maintaining s…
Visual Hand Gesture Recognition with Deep Learning: A Comprehensive Review of Methods, Datasets, Challenges and Future Research Directions
Konstantinos Foteinos, Manousos Linardakis, Panagiotis Radoglou-Grammatikis +4
The rapid evolution of deep learning (DL) models and the ever-increasing size of available datasets have raised the interest of the research community in the always-important field…
Enhancing Manufacturing Training Through VR Simulations
Vladislav Li, Ilias Siniosoglou, Panagiotis Sarigiannidis +1
In contemporary training for industrial manufacturing, reconciling theoretical knowledge with practical experience continues to be a significant difficulty. As companies transition…
X-ray illicit object detection using hybrid CNN-transformer neural network architectures
Jorgen Cani, Christos Diou, Spyridon Evangelatos +5
In the field of X-ray security applications, even the smallest details can significantly impact outcomes. Objects that are heavily occluded or intentionally concealed pose a great…
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…
Public space security management using digital twin technologies
Stylianos Zindros, Christos Chronis, Panagiotis Radoglou-Grammatikis +4
As the security of public spaces remains a critical issue in today's world, Digital Twin technologies have emerged in recent years as a promising solution for detecting and predict…
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…
NeuroXVocal: Detection and Explanation of Alzheimer's Disease through Non-invasive Analysis of Picture-prompted Speech
Nikolaos Ntampakis, Konstantinos Diamantaras, Ioanna Chouvarda +3
The early diagnosis of Alzheimer's Disease (AD) through non invasive methods remains a significant healthcare challenge. We present NeuroXVocal, a novel dual-component system that…
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…
Enhancing 3D Object Detection in Autonomous Vehicles Based on Synthetic Virtual Environment Analysis
Vladislav Li, Ilias Siniosoglou, Thomai Karamitsou +6
Autonomous Vehicles (AVs) use natural images and videos as input to understand the real world by overlaying and inferring digital elements, facilitating proactive detection in an e…
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…
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…