9 citations · 12 across the 14 of their papers we have counts for
16 papers
When Minute-Resolution Monitoring Meets Session-Level Injury Labels: Landmark-Based Discrimination in Elite Women's Football
Evangelos Chatzidimitriou, Konstantinos Tserpes
Minute-resolution athlete monitoring is increasingly common, while injury annotation may exist only at the athlete-session level and omit within-session onset time. Replicating a p…
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…
A Comparative Analysis on the Performance of Upper Confidence Bound Algorithms in Adaptive Deep Neural Networks
Grigorios Papanikolaou, Ioannis Kontopoulos, Konstantinos Tserpes
Edge computing environments impose strict constraints on energy consumption and latency, making the deployment of deep neural networks a significant challenge. Therefore, smart and…
Video Reconstruction using Diffusion-based Image-to-Video Generation with Trajectory Guidance
Stelio Bompai, Ioannis Kontopoulos, Giannis Spiliopoulos +2
This paper addresses the problem of reconstructing missing or dropped frames in top-down drone video of autonomous surface vehicles performing structured maritime manoeuvres. We pr…
Enabling Adversarial Robustness in AI Models through Kubeflow MLOps
Stavros Bouras, Ioannis Korontanis, Antonios Makris +1
AI models are increasingly deployed in cloud-native environments to support scalable and automated services. However, while platforms such as Kubernetes provide strong infrastructu…
Privacy Evaluation of Generative Models for Trajectory Generation
Stavros Bouras, Ioannis Kontopoulos, Chiara Pugliese +5
Trajectory data is fundamental to modern urban intelligence, yet its sensitivity raises significant privacy concerns. Generative models such as Generative Adversarial Networks, Var…
Trajectory-Aware Adaptive Inference in Object Detection Models
Grigorios Papanikolaou, Ioannis Kontopoulos, Giannis Spiliopoulos +2
The increasing integration of sensors in autonomous maritime navigation has led to large-scale multimodal datasets, raising challenges in achieving efficient real-time perception.…
A Comparative Study of Federated Learning Aggregation Strategies under Homogeneous and Heterogeneous Data Distributions
Antonios Makris, Christos Dousis, Emmanouil Kritharakis +2
Federated Learning has emerged as a transformative paradigm for collaborative machine learning across distributed environments. However, its performance is strongly influenced by t…
FedGreed: A Byzantine-Robust Loss-Based Aggregation Method for Federated Learning
Emmanouil Kritharakis, Antonios Makris, Dusan Jakovetic +1
Federated Learning (FL) enables collaborative model training across multiple clients while preserving data privacy by keeping local datasets on-device. In this work, we address FL…
Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering
Emmanouil Kritharakis, Dusan Jakovetic, Antonios Makris +1
Federated Learning (FL) enables collaborative model training across multiple clients without sharing private data. We consider FL scenarios wherein FL clients are subject to advers…
A New Approach for Evaluating the Performance of Distributed Latency-Sensitive Services
Theodoros Theodoropoulos, John Violos, Antonios Makris +1
Conventional latency metrics are formulated based on a broad definition of traditional monolithic services, and hence lack the capacity to address the complexities inherent in mode…
Converter: A CEAML Reasoner Python package to Streamline Orchestration Across Cloud and Edge Continuum
Ioannis Korontanis, Antonios Makris, Konstantinos Tserpes
In recent years, there has been a concerted effort in both industry and research sectors to innovate new approaches to DevOps. The primary aim is to facilitate developers in transi…
Graph Neural Networks and Reinforcement Learning for Proactive Application Image Placement
Antonios Makris, Theodoros Theodoropoulos, Evangelos Psomakelis +4
The shift from Cloud Computing to a Cloud-Edge continuum presents new opportunities and challenges for data-intensive and interactive applications. Edge computing has garnered a lo…
WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting
Theodoros Theodoropoulos, Angelos-Christos Maroudis, Antonios Makris +1
Regional traffic forecasting is a critical challenge in urban mobility, with applications to various fields such as the Internet of Everything. In recent years, spatio-temporal gra…
Cross-Cluster Networking to Support Extended Reality Services
Theodoros Theodoropoulos, Luis Rosa, Abderrahmane Boudi +6
Extented Reality (XR) refers to a class of contemporary services that are intertwined with a plethora of rather demanding Quality of Service (QoS) and functional requirements. Desp…
Intelligent Proactive Fault Tolerance at the Edge through Resource Usage Prediction
Theodoros Theodoropoulos, John Violos, Stylianos Tsanakas +3
The proliferation of demanding applications and edge computing establishes the need for an efficient management of the underlying computing infrastructures, urging the providers to…