Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Vaia Rousopoulou"'
Autor:
Vaia Rousopoulou, Alexandros Nizamis, Thanasis Vafeiadis, Dimosthenis Ioannidis, Dimitrios Tzovaras
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
The exploitation of big volumes of data in Industry 4.0 and the increasing development of cognitive systems strongly facilitate the realm of predictive maintenance for real-time decisions and early fault detection in manufacturing and production. Cog
Externí odkaz:
https://doaj.org/article/d3af424f66ae4988b1e357407c70fe48
Autor:
Christoph Mertens, Jesús Alonso, Oscar Lázaro, Charaka Palansuriya, Gernot Böge, Alexandros Nizamis, Vaia Rousopoulou, Dimosthenis Ioannidis, Dimitrios Tzovaras, Rizkallah Touma, Miquel Tarzán, Diego Mallada, Paulo Figueiras, Ruben Costa, Diogo Graça, Gisela Garcia, Begoña Laibarra, Aitor Celaya, Piotr Sobonski, Azzam Naeem, Alberto Mozo, Stanislav Vakaruk, J. Enrique Sierra-García, Antonio Pastor, Juan Rodriguez, Marlène Hildebrand, Tomasz Luniewski, Wojciech Zietak, Christoph Lange, Konstantinos Sipsas, Athanasios Poulakidas
Publikováno v:
Data Spaces ISBN: 9783030986353
The path that the European Commission foresees to leverage data in the best possible way for the sake of European citizens and the digital single market clearly addresses the need for a European Data Space. This data space must follow the rules, deri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::001cc88ff276cb6e5bcec73d1ea89b6d
https://doi.org/10.1007/978-3-030-98636-0_10
https://doi.org/10.1007/978-3-030-98636-0_10
Autor:
Dimosthenis Ioannidis, Leonidas Samaras, Vaia Rousopoulou, Ioannis Iakovidis, Alexandros Nizamis, Dimitrios Tzovaras, Konstantinos Georgiadis, Thanasis Vafeiadis, Alkis Kirtsoglou
Publikováno v:
Computers in Industry. 134:103555
This work presents a cognitive analytics platform for anomaly detection which is capable to handle, analyze and exploit resourcefully machine data from a shop-floor of factory, so as to support the emerging and growing needs of manufacturing industry
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::671a2ac4c716cdeba5df9e61c8b104ab
https://doi.org/10.1016/j.compind.2021.103555
https://doi.org/10.1016/j.compind.2021.103555
Autor:
Alexandros Nizamis, Thanasis Vafeiadis, Vaia Rousopoulou, Dimitrios Tzovaras, Vissarion Pavlopoulos, Luigi Giugliano, Dimosthenis Ioannidis
Publikováno v:
DCOSS
2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS)
2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS)
Today, the use of IoT devices, the inter-connectivity of machines and systems, and the development of novel analytic algorithms which are main characteristics of Industry 4.0 are also transferred to other domains connected to the industrial one. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1e2f68680fabc11ded131478a090da7
https://doi.org/10.1109/dcoss.2019.00074
https://doi.org/10.1109/dcoss.2019.00074
Autor:
Konstantinos Papachristou, Nikolaos Dimitriou, Anastasios Drosou, Vaia Rousopoulou, Dimitrios Tzovaras
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030349943
ICVS
ICVS
The 3D reconstruction of Cultural Heritage objects is a significant and advantageous technology for conservators and restorers. It contributes to the proper documentation of CH items, allows researchers, scholars and the general public to better mani
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7e1b7f4f9ca072b987c8e504233e194
https://doi.org/10.1007/978-3-030-34995-0_39
https://doi.org/10.1007/978-3-030-34995-0_39
Autor:
Vaia Rousopoulou, Peter Haigh, Luigi Giugliano, Dimosthenis Ioannidis, Alexandros Nizamis, Dimitrios Tzovaras, Luis Martins
Publikováno v:
Lecture Notes in Business Information Processing ISBN: 9783030209476
CAiSE Workshops
CAiSE Workshops
In Industry 4.0, predictive maintenance aims to improve both production and maintenance efficiency. The interconnected machines and IoT devices produce a variety of data that enable the early detection of anomalies and failures by predictive analytic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c654934846441e0126cd5911aa169d59
https://doi.org/10.1007/978-3-030-20948-3_8
https://doi.org/10.1007/978-3-030-20948-3_8
Autor:
Thanasis Vafeiadis, Vaia Rousopoulou, Dimosthenis Ioannidis, Dimitrios Tzovaras, Alexandros Nizamis
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
Frontiers in Artificial Intelligence
Frontiers in Artificial Intelligence
The exploitation of big volumes of data in Industry 4.0 and the increasing development of cognitive systems strongly facilitate the realm of predictive maintenance for real-time decisions and early fault detection in manufacturing and production. Cog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64b2064d05341ab168acbd5912e8ed90