Zobrazeno 1 - 10
of 11 238
pro vyhledávání: '"Aris, P"'
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 heterogeneity in autonomous vehicle environments by proposing a personali
Externí odkaz:
http://arxiv.org/abs/2411.04692
This paper proposes a novel localization framework based on collaborative training or federated learning paradigm, for highly accurate localization of autonomous vehicles. More specifically, we build on the standard approach of KalmanNet, a recurrent
Externí odkaz:
http://arxiv.org/abs/2411.05847
Autor:
Gkillas, Alexandros, Lalos, Aris
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, however the improved detection accuracy is achieved with the utilization of
Externí odkaz:
http://arxiv.org/abs/2411.03996
Autor:
Aristorenas, Aris J.
This study presents a machine learning framework for assessing similarity between audio content and predicting sentiment score. We construct a dataset containing audio samples from music covers on YouTube along with the audio of the original song, an
Externí odkaz:
http://arxiv.org/abs/2411.00195
MIMO MAC Empowered by Reconfigurable Intelligent Surfaces: Capacity Region and Large System Analysis
Smart wireless environments enabled by multiple distributed Reconfigurable Intelligent Surfaces (RISs) have recently attracted significant research interest as a wireless connectivity paradigm for sixth Generation (6G) networks. In this paper, using
Externí odkaz:
http://arxiv.org/abs/2410.07389
Autor:
Tatli, Dimitra, Papapanagiotou, Vasileios, Liakos, Aris, Tsapas, Apostolos, Delopoulos, Anastasios
Prediabetes is a common health condition that often goes undetected until it progresses to type 2 diabetes. Early identification of prediabetes is essential for timely intervention and prevention of complications. This research explores the feasibili
Externí odkaz:
http://arxiv.org/abs/2410.02692
Low Earth Orbit Satellite Networks (LSNs) are integral to supporting a broad range of modern applications, which are typically modeled as Service Function Chains (SFCs). Each SFC is composed of Virtual Network Functions (VNFs), where each VNF perform
Externí odkaz:
http://arxiv.org/abs/2409.05025
3D pose estimation from a 2D cross-sectional view enables healthcare professionals to navigate through the 3D space, and such techniques initiate automatic guidance in many image-guided radiology applications. In this work, we investigate how estimat
Externí odkaz:
http://arxiv.org/abs/2408.09931
Network Function Virtualization (NFV) has shifted communication networks towards more adaptable software solutions, but this transition raises new security concerns, particularly in public cloud deployments. While Intel's Software Guard Extensions (S
Externí odkaz:
http://arxiv.org/abs/2408.02212
We construct a weakly compact convex subset of $\ell^2$ with nonempty interior that has an isolated maximal element, with respect to the lattice order $\ell _+^2$. Moreover, the maximal point cannot be supported by any strictly positive functional, s
Externí odkaz:
http://arxiv.org/abs/2407.10509