Zobrazeno 1 - 10
of 272
pro vyhledávání: '"ROVETTA, S."'
Yes
Data streams have arisen as a relevant research topic during the past decade. They are real‐time, incremental in nature, temporally ordered, massive, contain outliers, and the objects in a data stream may evolve over time (concept drift).
Data streams have arisen as a relevant research topic during the past decade. They are real‐time, incremental in nature, temporally ordered, massive, contain outliers, and the objects in a data stream may evolve over time (concept drift).
Externí odkaz:
http://hdl.handle.net/10454/17599
Yes
Multidimensional data streams are a major paradigm in data science. This work focuses on possibilistic clustering algorithms as means to perform clustering of multidimensional streaming data. The proposed approach exploits fuzzy outlier anal
Multidimensional data streams are a major paradigm in data science. This work focuses on possibilistic clustering algorithms as means to perform clustering of multidimensional streaming data. The proposed approach exploits fuzzy outlier anal
Externí odkaz:
http://hdl.handle.net/10454/17629
Yes
Real time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taki
Real time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taki
Externí odkaz:
http://hdl.handle.net/10454/17627
Yes
Data streams have arisen as a relevant topic during the last few years as an efficient method for extracting knowledge from big data. In the robust layered ensemble model (RLEM) proposed in this paper for short-term traffic flow forecasting,
Data streams have arisen as a relevant topic during the last few years as an efficient method for extracting knowledge from big data. In the robust layered ensemble model (RLEM) proposed in this paper for short-term traffic flow forecasting,
Externí odkaz:
http://hdl.handle.net/10454/17598
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Iranian Journal of Science; February 2023, Vol. 47 Issue: 1 p175-186, 12p
Publikováno v:
In Fuzzy Sets and Systems 2005 152(1):37-48
Autor:
Imangaliyev, S., van der Veen, M.H., Volgenant, C.M.C., Loos, B.G., Keijser, B.J.F., Crielaard, W., Levin, E., Lintas, A., Rovetta, S., Verschure, P.F.M.J., Villa, A.E.P.
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017 : proceedings, 778-779
STARTPAGE=778;ENDPAGE=779;TITLE=Artificial Neural Networks and Machine Learning – ICANN 2017
Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017 : proceedings, 2, 778-779
STARTPAGE=778;ENDPAGE=779;TITLE=Artificial Neural Networks and Machine Learning – ICANN 2017
Artificial Neural Networks and Machine Learning – ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy, September 11-14, 2017 : proceedings, 2, 778-779
Images are an important data source for diagnosis of oral diseases. The manual classification of images may lead to suboptimal treatment procedures due to subjective errors. In this paper an image classification algorithm based on Deep Learning frame
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::087ed2850bba1971d78c2ef41366fcb7
https://research.vu.nl/en/publications/7e7fe29a-38c0-4c06-a1a6-c8efadb57861
https://research.vu.nl/en/publications/7e7fe29a-38c0-4c06-a1a6-c8efadb57861
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.