Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Konstantinos Psychogyios"'
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
Publikováno v:
IEEE Access, Vol 11, Pp 21562-21574 (2023)
Electronic health records (EHR) are patient-level information, e.g., laboratory tests and questionnaires, stored in electronic format. Compared to physical records, the EHR alternative allows patients to access their data easily and helps staff with
Externí odkaz:
https://doaj.org/article/6a3685fc71a340bf9db964ef99427319
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:
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
