Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Stavroula Bourou"'
Publikováno v:
Telecom, Vol 5, Iss 1, Pp 1-20 (2023)
Safety management is a priority to guarantee human-centered manufacturing processes in the context of Industry 5.0, which aims to realize a safe human–machine environment based on knowledge-driven approaches. The traditional approaches for safety m
Externí odkaz:
https://doaj.org/article/6ede413b0d834cf4a0e973e74e439728
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
Autor:
Konstantinos Psychogyios, Helen C. Leligou, Filisia Melissari, Stavroula Bourou, Zacharias Anastasakis, Theodore Zahariadis
Publikováno v:
IEEE Access, Vol 11, Pp 100256-100267 (2023)
Neural Style Transfer (NST) is a popular technique of computer vision where the content of an image is blended with the style of another, which results in a fused image with certain properties of both original images. This approach has practical appl
Externí odkaz:
https://doaj.org/article/d5c6f3cad6864b15ba2ff9d8cc727aad
Autor:
Konstantinos Psychogyios, Andreas Papadakis, Stavroula Bourou, Nikolaos Nikolaou, Apostolos Maniatis, Theodore Zahariadis
Publikováno v:
Future Internet, Vol 16, Iss 3, p 73 (2024)
The advent of computer networks and the internet has drastically altered the means by which we share information and interact with each other. However, this technological advancement has also created opportunities for malevolent behavior, with indivi
Externí odkaz:
https://doaj.org/article/727f3a6b49d24d8dacf137a0aff7e205
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:
Athanasios Psaltis, Kassiani Zafeirouli, Peter Leškovský, Stavroula Bourou, Juan Camilo Vásquez-Correa, Aitor García-Pablos, Santiago Cerezo Sánchez, Anastasios Dimou, Charalampos Z. Patrikakis, Petros Daras
Publikováno v:
Information, Vol 14, Iss 6, p 342 (2023)
The present study thoroughly evaluates the most common blocking challenges faced by the federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system adaptation pipeline is designed to enable the integration of differen
Externí odkaz:
https://doaj.org/article/38e93b300ad5467d8b02391d19d161be
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
Autor:
Daras, Athanasios Psaltis, Kassiani Zafeirouli, Peter Leškovský, Stavroula Bourou, Juan Camilo Vásquez-Correa, Aitor García-Pablos, Santiago Cerezo Sánchez, Anastasios Dimou, Charalampos Z. Patrikakis, Petros
Publikováno v:
Information; Volume 14; Issue 6; Pages: 342
The present study thoroughly evaluates the most common blocking challenges faced by the federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system adaptation pipeline is designed to enable the integration of differen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::4f7a6e4aaf9720823387d3baaab3d949
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
Publikováno v:
Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications.
In recent years, Artificial Intelligence (AI) technology has seen significant growth due to advancements in machine learning (ML) and data processing, as well as the availability of large amounts of data. The integration of AI with eXtended Reality (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8423ee01f64c236f7b3d92d639d658e0
https://doi.org/10.54941/ahfe1002938
https://doi.org/10.54941/ahfe1002938