Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Dimitrios Mavroeidis"'
Autor:
Mark Ramaekers, Christiaan G. A. Viviers, Boris V. Janssen, Terese A. E. Hellström, Lotte Ewals, Kasper van der Wulp, Joost Nederend, Igor Jacobs, Jon R. Pluyter, Dimitrios Mavroeidis, Fons van der Sommen, Marc G. Besselink, Misha D. P. Luyer
Publikováno v:
Journal of Clinical Medicine, Vol 12, Iss 13, p 4209 (2023)
Radiological imaging plays a crucial role in the detection and treatment of pancreatic ductal adenocarcinoma (PDAC). However, there are several challenges associated with the use of these techniques in daily clinical practice. Determination of the pr
Externí odkaz:
https://doaj.org/article/f754364a9150439891d0cd904ea2ac6e
Autor:
Lotte J. S. Ewals, Kasper van der Wulp, Ben E. E. M. van den Borne, Jon R. Pluyter, Igor Jacobs, Dimitrios Mavroeidis, Fons van der Sommen, Joost Nederend
Publikováno v:
Journal of Clinical Medicine, Vol 12, Iss 10, p 3536 (2023)
To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists, many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are currently being implemented in clinical practice, but the question is wheth
Externí odkaz:
https://doaj.org/article/e0b8ec3830fd4ed698c9a0fde5552e62
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
Image Analysis and Processing – ICIAP 2022 ISBN: 9783031064326
Egocentric action anticipation consists in predicting a future action the camera wearer will perform from egocentric video. While the task has recently attracted the attention of the research community, current approaches assume that the input videos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9c725c1a519127d1fa2d56046372e90
http://arxiv.org/abs/2202.04132
http://arxiv.org/abs/2202.04132
Publikováno v:
Engineering Applications of Artificial Intelligence. 114:105140
Egocentric videos can bring a lot of information about how humans perceive the world and interact with the environment, which can be beneficial for the analysis of human behaviour. The research in egocentric video analysis is developing rapidly thank
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8113a19a9becf3c69d9e73d7d78c1b79
Autor:
Ralf Hoffmann, Monique Hendriks, Pieter C. Vos, Sergio Consoli, Jacek Kustra, Dimitrios Mavroeidis
Publikováno v:
Machine Learning, Optimization, and Data Science ISBN: 9783030137083
LOD
LOD
Data analytics methods in the clinical domain are challenging to put into practice. Unsupervised learning provides opportunity for giving the level of personalization in evidence based decision-making that can otherwise only be achieved through the u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1f2bd3901b16d75e6de196c1b825a7b
https://doi.org/10.1007/978-3-030-13709-0_26
https://doi.org/10.1007/978-3-030-13709-0_26
Autor:
Tobias Klinder, Homer H. Pien, Christoph Wald, Stojan Trajanovski, Binyam Gebrekidan Gebre, Brady McKee, Sebastian Flacke, Bastiaan S. Veeling, Heber MacMahon, Shawn Regis, Dimitrios Mavroeidis, Rafael Wiemker, Amir M. Tahmasebi, Christine Leon Swisher
Importance: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and it has been recently demonstrated that low-dose computed tomography (CT) screening o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1d9dfe04178289cdc15323caaeb71c5
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319729251
MOD
MOD
In this paper, we propose a method for optimization of the parameters of a Support Vector Machine which is more accurate than the usually applied grid search method. The method is based on Iterated Local Search, a classic metaheuristic that performs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ecbc8e293d7382e5c62e42b189c91b93
https://doi.org/10.1007/978-3-319-72926-8_2
https://doi.org/10.1007/978-3-319-72926-8_2
Publikováno v:
Transportation Research Record: Journal of the Transportation Research Board. 2491:81-89
The problem of modeling traffic in urban areas is especially relevant because of the urgent need for managing congestion in big cities. In recent years, the macroscopic fundamental diagram (MFD) has been proposed as a macroscopic description of urban