Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Vasileios Sevetlidis"'
Publikováno v:
IEEE Access, Vol 12, Pp 90287-90298 (2024)
In this study, a novel approach for solving the PU learning problem is proposed based on an anomaly detection strategy. A Convolutional Autoencoder (CAE) is used to extract latent encodings from positive-labeled data, which are then linearly combined
Externí odkaz:
https://doaj.org/article/edfb823878e542858f6f7adafb7314e0
Publikováno v:
Computers, Vol 13, Iss 2, p 49 (2024)
Identifying accidents in road black spots is crucial for improving road safety. Traditional methodologies, although insightful, often struggle with the complexities of imbalanced datasets, while machine learning (ML) techniques have shown promise, ou
Externí odkaz:
https://doaj.org/article/307ff1d119264f7d9f5a81392b0e9c64
Publikováno v:
IEEE Access, Vol 10, Pp 126832-126844 (2022)
The early 21st-century technological advancements tilted the scales towards data-driven learning. Thus, modern machine-learning systems rely heavily on data to learn complex models to efficiently provide relevant predictions. Data-driven learning suf
Externí odkaz:
https://doaj.org/article/bbf428979f014a92ad77d3c88d8a0091
Autor:
Ioannis Karamanlis, Alexandros Kokkalis, Vassilios Profillidis, George Botzoris, Chairi Kiourt, Vasileios Sevetlidis, George Pavlidis
Publikováno v:
Data, Vol 8, Iss 6, p 110 (2023)
Black spot identification, a spatiotemporal phenomenon, involves analysing the geographical location and time-based occurrence of road accidents. Typically, this analysis examines specific locations on road networks during set time periods to pinpoin
Externí odkaz:
https://doaj.org/article/7145b8096f4544bf87f07a63fc13fda5
Autor:
Dimitrios Karamatskos, Vasileios Arampatzakis, Vasileios Sevetlidis, Stavros Nousias, Athanasios Kalogeras, Christos Koulamas, Aris Lalos, George Pavlidis
Archaeologists, as well as specialists and practitioners in cultural heritage, require applications with additional functions, such as the annotation and attachment of metadata to specific regions of the 3D digital artifacts, to go beyond the simplis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdfa12b6eb2a932c8bf9abf8d5afc35d
Autor:
Konstantinos A. Tsintotas, Vasileios Sevetlidis, Ioannis Tsampikos Papapetros, Vasiliki Balaska, Athanasios Psomoulis, Antonios Gasteratos
Publikováno v:
2022 30th Mediterranean Conference on Control and Automation (MED).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4df778ed9234a558c7541355abb556b
https://doi.org/10.1109/med54222.2022.9837138
https://doi.org/10.1109/med54222.2022.9837138
Publikováno v:
25th Pan-Hellenic Conference on Informatics.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b4a2d30070996bcea11c0e17c5976dd
https://doi.org/10.1145/3503823.3503905
https://doi.org/10.1145/3503823.3503905
Autor:
Vasileios Arampatzakis, Vasileios Sevetlidis, Fotis Arnaoutoglou, Athanasios Kalogeras, Christos Koulamas, Aris Lalos, Chairi Kiourt, George Ioannakis, Anestis Koutsoudis, George Pavlidis
Beyond the simplistic three-dimensional (3D) visualisation, archaeologists, as well as cultural heritage experts and practitioners, need applications with advanced functionalities, such as the annotation and the attachment of metadata on particular r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::025d71b4cf3a795a7d632fb1ac0654d0
Autor:
George Pavlidis, Vasileios Sevetlidis
Publikováno v:
Journal of Cultural Heritage. 37:121-128
Treatment of spectral information is an essential tool for the examination of various cultural heritage materials. Raman spectroscopy has become an everyday practice for compound identification due to its non-intrusive nature, but often it can be a c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::687cd5e747d786030fa6844ceb004c56
https://doi.org/10.1016/j.culher.2018.10.016
https://doi.org/10.1016/j.culher.2018.10.016
Autor:
Vasileios Sevetlidis, Chairi Kiourt, Vassilis Katsouros, Alexandra D. Solomou, Spyridoula Stamouli, George Pavlidis, Kosmas Kritsis, George Karetsos
Publikováno v:
Sustainability, Vol 13, Iss 11865, p 11865 (2021)
Sustainability
Volume 13
Issue 21
Sustainability
Volume 13
Issue 21
Plant identification from images has become a rapidly developing research field in com- puter vision and is particularly challenging due to the morphological complexity of plants. The availability of large databases of plant images, and the research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd6824b2ca8a8b95a39ebb9c17618f81
https://doi.org/10.3390/su132111865
https://doi.org/10.3390/su132111865