71 citations · 147 across the 25 of their papers we have counts for
25 papers
CDKF-Track: Cluster-aware Data-Driven Kalman Filtering for Cooperative 3D Multi-Object Tracking
Maria Damanaki, Nikos Piperigkos, Alexandros Gkillas +1
Multi-Object Tracking (MOT) is essential for EdgeAI perception systems, where accurate object localization and reliable identification enable safe decision-making. Singleagent MOT…
Adversarially Guided Diffusion for LiDAR Range Image Synthesis
Stavros Bouras, Antonios Makris, Alexandros Gkillas +2
LiDAR semantic segmentation is a key perception task in autonomous driving, where false predictions can affect downstream planning and safety-critical decision-making. Although adv…
Fast and Accurate Outlier-Aware LiDAR Super-Resolution for SLAM Applications
Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1
This work tackles the challenge of enhancing low-resolution LiDAR sensors for SLAM applications through a novel Deep Unrolling-based Super-Resolution (SR) model. We integrate an ou…
Guided Model-based LiDAR Super-Resolution for Resource-Efficient Automotive scene Segmentation
Alexandros Gkillas, Nikos Piperigkos, Aris S. Lalos
High-resolution LiDAR data plays a critical role in 3D semantic segmentation for autonomous driving, but the high cost of advanced sensors limits large-scale deployment. In contras…
Integrated Simulation Framework for Adversarial Attacks on Autonomous Vehicles
Christos Anagnostopoulos, Ioulia Kapsali, Alexandros Gkillas +2
Autonomous vehicles (AVs) rely on complex perception and communication systems, making them vulnerable to adversarial attacks that can compromise safety. While simulation offers a…
Efficient Model-Based Purification Against Adversarial Attacks for LiDAR Segmentation
Alexandros Gkillas, Ioulia Kapsali, Nikos Piperigkos +1
LiDAR-based segmentation is essential for reliable perception in autonomous vehicles, yet modern segmentation networks are highly susceptible to adversarial attacks that can compro…
A holistic perception system of internal and external monitoring for ground autonomous vehicles: AutoTRUST paradigm
Alexandros Gkillas, Christos Anagnostopoulos, Nikos Piperigkos +16
This paper introduces a holistic perception system for internal and external monitoring of autonomous vehicles, with the aim of demonstrating a novel AI-leveraged self-adaptive fra…
Robustifying 3D Perception via Least-Squares Graphs for Multi-Agent Object Tracking
Maria Damanaki, Ioulia Kapsali, Nikos Piperigkos +2
The critical perception capabilities of EdgeAI systems, such as autonomous vehicles, are required to be resilient against adversarial threats, by enabling accurate identification a…
Optimizing Cooperative Multi-Object Tracking using Graph Signal Processing
Maria Damanaki, Nikos Piperigkos, Alexandros Gkillas +1
Multi-Object Tracking (MOT) plays a crucial role in autonomous driving systems, as it lays the foundations for advanced perception and precise path planning modules. Nonetheless, s…
Personalized Federated Learning for Cross-view Geo-localization
Christos Anagnostopoulos, Alexandros Gkillas, Nikos Piperigkos +1
In this paper we propose a methodology combining Federated Learning (FL) with Cross-view Image Geo-localization (CVGL) techniques. We address the challenges of data privacy and het…
Towards Resource-Efficient Federated Learning in Industrial IoT for Multivariate Time Series Analysis
Alexandros Gkillas, Aris Lalos
Anomaly and missing data constitute a thorny problem in industrial applications. In recent years, deep learning enabled anomaly detection has emerged as a critical direction, howev…
Federated Data-Driven Kalman Filtering for State Estimation
Nikos Piperigkos, Alexandros Gkillas, Christos Anagnostopoulos +1
This paper proposes a novel localization framework based on collaborative training or federated learning paradigm, for highly accurate localization of autonomous vehicles. More spe…
Real time enhancement of operator's ergonomics in physical human-robot collaboration scenarios using a multi-stereo camera system
Gerasimos Arvanitis, Nikos Piperigkos, Christos Anagnostopoulos +2
In collaborative tasks where humans work alongside machines, the robot's movements and behaviour can have a significant impact on the operator's safety, health, and comfort. To add…
Fast mesh denoising with data driven normal filtering using deep variational autoencoders
Stavros Nousias, Gerasimos Arvanitis, Aris S. Lalos +1
Recent advances in 3D scanning technology have enabled the deployment of 3D models in various industrial applications like digital twins, remote inspection and reverse engineering.…
Fast Spatio-temporal Compression of Dynamic 3D Meshes
Gerasimos Arvanitis, Aris S. Lalos, Konstantinos Moustakas
3D representations of highly deformable 3D models, such as dynamic 3D meshes, have recently become very popular due to their wide applicability in various domains. This trend inevi…
Graph Laplacian Diffusion Localization of Connected and Automated Vehicles
Nikos Piperigkos, Aris S. Lalos, Kostas Berberidis
In this paper, we design distributed multi-modal localization approaches for Connected and Automated vehicles. We utilize information diffusion on graphs formed by moving vehicles,…
Accelerating deep neural networks for efficient scene understanding in automotive cyber-physical systems
Stavros Nousias, Erion-Vasilis Pikoulis, Christos Mavrokefalidis +1
Automotive Cyber-Physical Systems (ACPS) have attracted a significant amount of interest in the past few decades, while one of the most critical operations in these systems is the…
A New Clustering-Based Technique for the Acceleration of Deep Convolutional Networks
Erion-Vasilis Pikoulis, Christos Mavrokefalidis, Aris S. Lalos
Deep learning and especially the use of Deep Neural Networks (DNNs) provides impressive results in various regression and classification tasks. However, to achieve these results, t…
Efficient automated U-Net based tree crown delineation using UAV multi-spectral imagery on embedded devices
Kostas Blekos, Stavros Nousias, Aris S Lalos
Delineation approaches provide significant benefits to various domains, including agriculture, environmental and natural disasters monitoring. Most of the work in the literature ut…
Cooperative Multi-Modal Localization in Connected and Autonomous Vehicles
Nikos Piperigkos, Aris S. Lalos, Kostas Berberidis +1
Cooperative Localization is expected to play a crucial role in various applications in the field of Connected and Autonomous vehicles (CAVs). Future 5G wireless systems are expecte…
Empowering cyberphysical systems of systems with intelligence
Stavros Nousias, Nikos Piperigkos, Gerasimos Arvanitis +3
Cyber Physical Systems have been going into a transition phase from individual systems to a collecttives of systems that collaborate in order to achieve a highly complex cause, rea…
Enhancing an eco-driving gamification platform through wearable and vehicle sensor data integration
Christos Tselios, Stavros Nousias, Dimitris Bitzas +5
As road transportation has been identified as a major contributor of environmental pollution, motivating individuals to adopt a more eco-friendly driving style could have a substan…
Block-Based Spectral Processing of Static and Dynamic 3D Meshes using Orthogonal Iterations
Gerasimos Arvanitis, Aris S. Lalos, Konstantinos Moustakas
Spectral methods are widely used in geometry processing of 3D models. They rely on the projection of the mesh geometry on the basis defined by the eigenvectors of the graph Laplaci…
Information Exchange in Randomly Deployed Dense WSNs with Wireless Energy Harvesting Capabilities
Prodromos-Vasileios Mekikis, Angelos Antonopoulos, Elli Kartsakli +3
As large-scale dense and often randomly deployed wireless sensor networks (WSNs) become widespread, local information exchange between co-located sets of nodes may play a significa…