2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
Cross-layer Theoretical Analysis of NC-aided Cooperative ARQ Protocols in Correlated Shadowed Environments (Extended Version)
Angelos Antonopoulos, Aris S. Lalos, Marco Di Renzo +1
In this paper, we propose a cross-layer analytical model for the study of Network Coding (NC)-based Automatic Repeat reQuest (ARQ) Medium Access Control (MAC) protocols in correlat…