Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Papadopoulos, Georgios Th."'
Autor:
Siniosoglou, Ilias, Argyriou, Vasileios, Fragulis, George, Fouliras, Panagiotis, Papadopoulos, Georgios Th., Lytos, Anastasios, Sarigiannidis, Panagiotis
The time-consuming nature of training and deploying complicated Machine and Deep Learning (DL) models for a variety of applications continues to pose significant challenges in the field of Machine Learning (ML). These challenges are particularly pron
Externí odkaz:
http://arxiv.org/abs/2409.06904
Autor:
Koletsis, Panagiotis, Gemos, Panagiotis-Konstantinos, Chronis, Christos, Varlamis, Iraklis, Efthymiou, Vasilis, Papadopoulos, Georgios Th.
The rise of financial crime that has been observed in recent years has created an increasing concern around the topic and many people, organizations and governments are more and more frequently trying to combat it. Despite the increase of interest in
Externí odkaz:
http://arxiv.org/abs/2409.13704
Autor:
Stefanidou, Artemis, Cani, Jorgen, Papadopoulos, Thomas, Radoglou-Grammatikis, Panagiotis, Sarigiannidis, Panagiotis, Varlamis, Iraklis, Papadopoulos, Georgios Th.
Over the recent years, the protection of the so-called `soft-targets', i.e. locations easily accessible by the general public with relatively low, though, security measures, has emerged as a rather challenging and increasingly important issue. The co
Externí odkaz:
http://arxiv.org/abs/2408.17136
In the field of modern robotics, robots are proving to be useful in tackling high-risk situations, such as navigating hazardous environments like burning buildings, earthquake-stricken areas, or patrolling crime-ridden streets, as well as exploring u
Externí odkaz:
http://arxiv.org/abs/2407.14218
Autor:
Alimisis, Panagiotis, Mademlis, Ioannis, Radoglou-Grammatikis, Panagiotis, Sarigiannidis, Panagiotis, Papadopoulos, Georgios Th.
Image data augmentation constitutes a critical methodology in modern computer vision tasks, since it can facilitate towards enhancing the diversity and quality of training datasets; thereby, improving the performance and robustness of machine learnin
Externí odkaz:
http://arxiv.org/abs/2407.04103
Autor:
Mademlis, Ioannis, Cani, Jorgen, Mancuso, Marina, Paternoster, Caterina, Adamakis, Emmanouil, Margetis, George, Chambon, Sylvie, Crouzil, Alain, Lechelek, Loubna, Dede, Georgia, Evangelatos, Spyridon, Lalas, George, Mignet, Franck, Linardatos, Pantelis, Kentrotis, Konstantinos, Gierszal, Henryk, Tyczka, Piotr, Karagiorgou, Sophia, Pantelis, George, Stavropoulos, Georgios, Votis, Konstantinos, Papadopoulos, Georgios Th.
Modern technologies have led illicit firearms trafficking to partially merge with cybercrime, while simultaneously permitting its off-line aspects to become more sophisticated. Law enforcement officers face difficult challenges that require hi-tech s
Externí odkaz:
http://arxiv.org/abs/2406.14949
Robotic exploration has long captivated researchers aiming to map complex environments efficiently. Techniques such as potential fields and frontier exploration have traditionally been employed in this pursuit, primarily focusing on solitary agents.
Externí odkaz:
http://arxiv.org/abs/2405.20232
Autor:
Bouzinis, Pavlos S., Radoglou-Grammatikis, Panagiotis, Makris, Ioannis, Lagkas, Thomas, Argyriou, Vasileios, Papadopoulos, Georgios Th., Sarigiannidis, Panagiotis, Karagiannidis, George K.
Federated learning (FL) is a decentralized learning technique that enables participating devices to collaboratively build a shared Machine Leaning (ML) or Deep Learning (DL) model without revealing their raw data to a third party. Due to its privacy-
Externí odkaz:
http://arxiv.org/abs/2405.13062
Autor:
Konstantakos, Sotirios, Chalkiadaki, Despina Ioanna, Mademlis, Ioannis, Asano, Yuki M., Gavves, Efstratios, Papadopoulos, Georgios Th.
Self-Supervised Learning (SSL) is a valuable and robust training methodology for contemporary Deep Neural Networks (DNNs), enabling unsupervised pretraining on a `pretext task' that does not require ground-truth labels/annotation. This allows efficie
Externí odkaz:
http://arxiv.org/abs/2404.17202
Exploring Machine Learning Algorithms for Infection Detection Using GC-IMS Data: A Preliminary Study
Autor:
Sardianos, Christos, Symvoulidis, Chrysostomos, Schlögl, Matthias, Varlamis, Iraklis, Papadopoulos, Georgios Th.
The developing field of enhanced diagnostic techniques in the diagnosis of infectious diseases, constitutes a crucial domain in modern healthcare. By utilizing Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) data and incorporating machine learn
Externí odkaz:
http://arxiv.org/abs/2404.15757