Zobrazeno 1 - 10
of 122
pro vyhledávání: '"Voulkidis, A."'
Autor:
Konstantinos Prousalidis, Stavroula Bourou, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Aikaterini Zachariadi, Vassilios Zachariadis
Publikováno v:
Drones, Vol 8, Iss 8, p 408 (2024)
This paper addresses the challenge of olive tree segmentation using drone imagery, which is crucial for precision agriculture applications. We tackle the data scarcity issue by augmenting existing detection datasets. Additionally, lightweight model v
Externí odkaz:
https://doaj.org/article/d8033ea0c5b24d60be1ac89fa5d46a38
Akademický článek
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Autor:
Zacharias Anastasakis, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Stavroula Bourou, Konstantinos Psychogyios, Dimitrios Skias, Theodore Zahariadis
Publikováno v:
Future Internet, Vol 15, Iss 9, p 296 (2023)
Federated Learning is identified as a reliable technique for distributed training of ML models. Specifically, a set of dispersed nodes may collaborate through a federation in producing a jointly trained ML model without disclosing their data to each
Externí odkaz:
https://doaj.org/article/faf410db9c6f4ccf8a611478d34de8a5
Autor:
Konstantina Fotiadou, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Konstantinos Railis, Panagiotis Trakadas, Theodore Zahariadis
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 1, Pp 593-605 (2020)
Intrusion detection plays a critical role in cyber-security domain since malicious attacks cause irreparable damages to cyber-systems. In this work, we propose the I2SP prototype, which is a novel Information Sharing Platform, able to gather, pre-pro
Externí odkaz:
https://doaj.org/article/2127f023bbb64554990fe16026ad7ad0
Autor:
Stavroula Bourou, Andreas El Saer, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Theodore Zahariadis
Publikováno v:
Information, Vol 12, Iss 9, p 375 (2021)
Recent technological innovations along with the vast amount of available data worldwide have led to the rise of cyberattacks against network systems. Intrusion Detection Systems (IDS) play a crucial role as a defense mechanism in networks against adv
Externí odkaz:
https://doaj.org/article/52d919caf2624487bb7c951bd7e9b96f
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Konstantinos Psychogyios, Terpsichori-Helen Velivassaki, Stavroula Bourou, Artemis Voulkidis, Dimitrios Skias, Theodore Zahariadis
Publikováno v:
Electronics; Volume 12; Issue 8; Pages: 1805
Federated learning (FL) is an emerging machine learning technique where machine learning models are trained in a decentralized manner. The main advantage of this approach is the data privacy it provides because the data are not processed in a central
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::256323a06be08ab73609caa5c17c11ae
https://zenodo.org/record/7948139
https://zenodo.org/record/7948139
Autor:
Konstantina Fotiadou, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Dimitrios Skias, Sofia Tsekeridou, Theodore Zahariadis
Publikováno v:
Information, Vol 12, Iss 5, p 215 (2021)
Network intrusion detection is a key pillar towards the sustainability and normal operation of information systems. Complex threat patterns and malicious actors are able to cause severe damages to cyber-systems. In this work, we propose novel Deep Le
Externí odkaz:
https://doaj.org/article/55d3922e9afe43619db7d1788842f561
Autor:
Konstantina Fotiadou, Terpsichori Helen Velivassaki, Artemis Voulkidis, Dimitrios Skias, Corrado De Santis, Theodore Zahariadis
Publikováno v:
Energies, Vol 13, Iss 10, p 2622 (2020)
Autonomous fault detection plays a major role in the Critical Energy Infrastructure (CEI) domain, since sensor faults cause irreparable damage and lead to incorrect results on the condition monitoring of Cyber-Physical (CP) systems. This paper focuse
Externí odkaz:
https://doaj.org/article/d5c2fc51045b447ca16e00b40d3786d3
Autor:
Anastasakis, Zacharias, Psychogyios, Konstantinos, Velivassaki, Terpsichori-Helen, Bourou, Stavroula, Voulkidis, Artemis, Skias, Dimitrios, Gonos, Antonis, Zahariadis, Theodore
Nowadays, IoT networks and devices exist in our everyday life, capturing and carrying unlimited data. However, increasing penetration of connected systems and devices implies rising threats for cybersecurity with IoT systems suffering from network at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4bd2b469dabbcc95552245f97d2a636b
https://zenodo.org/record/7948086
https://zenodo.org/record/7948086