11 papers
From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond
Spyridon Evangelatos, Christos Diou, Georgios Th. Papadopoulos +2
Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of why a system behaves in a ce…
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…
Facial Expression Recognition in the Deep Learning Era: A Systematic Multi-Criteria Review of Methods, Models, Datasets, Performance, Challenges, and Future Research Directions
Spyridon Georgiou, Aggelos Psiris, Spyridon Evangelatos +5
Facial Expression Recognition (FER) has advanced rapidly over the last decade, driven by the shift from handcrafted descriptors and shallow classifiers to deep convolutional, atten…
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…
Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions
Aggelos Psiris, Vasileios Argyriou, Evangelos K. Markakis +6
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…
Open-Vocabulary vs Supervised Learning Methods for Post-Disaster Visual Scene Understanding
Anna Michailidou, Georgios Angelidis, Vasileios Argyriou +2
Aerial imagery is critical for large-scale post-disaster damage assessment. Automated interpretation remains challenging due to clutter, visual variability, and strong cross-event…