Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Dimitrios S. Frossyniotis"'
Autor:
Spiros Kintzios, C. P. Yialouris, Dimitrios S. Frossyniotis, Yannis Anthopoulos, Antonis Perdikaris
Publikováno v:
Artificial Neural Networks – ICANN 2006 ISBN: 9783540388715
ICANN (2)
ICANN (2)
Several researchers have shown that substantial improvements can be achieved in difficult pattern recognition problems by combining the outputs of multiple neural networks. In this work, we present and test a multi-net system for the detection of pla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a21701a68bd723bfeca6d0b02d8e9aff
https://doi.org/10.1007/11840930_41
https://doi.org/10.1007/11840930_41
Publikováno v:
International journal of neural systems. 15(5)
A multi-clustering fusion method is presented based on combining several runs of a clustering algorithm resulting in a common partition. More specifically, the results of several independent runs of the same clustering algorithm are appropriately com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::161d050b131fece75c822539cd71d802
https://pubmed.ncbi.nlm.nih.gov/16278943
https://pubmed.ncbi.nlm.nih.gov/16278943
Autor:
Andreas Stafylopatis, Konstantina S. Nikita, Dimitrios S. Frossyniotis, George L. Tsirogiannis
Publikováno v:
Methods and Applications of Artificial Intelligence ISBN: 9783540219378
SETN
SETN
Single classifiers, such as Neural Networks, Support Vector Machines, Decision Trees and other, can be used to perform classification of data for relatively simple problems. For more complex problems, combinations of simple classifiers can significan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::539c26b641ee8c016766d2c7e68dbd41
https://doi.org/10.1007/978-3-540-24674-9_17
https://doi.org/10.1007/978-3-540-24674-9_17
It is widely recognized that the boosting methodology provides superior results for classification problems. In this paper, we propose the boost-clustering algorithm which constitutes a novel clustering methodology that exploits the general principle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::caa560619ef8f9c50ff0f6ac0b8847a7
http://olympias.lib.uoi.gr/jspui/handle/123456789/10795
http://olympias.lib.uoi.gr/jspui/handle/123456789/10795
Publikováno v:
Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 ISBN: 9783540404088
ICANN
ICANN
The concept of semantic and context aware intelligent systems provides a vision for the Information Society where the emphasis lays on computing applications that can sense context from the people and the environment and wrap that knowledge into adap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b95032798364a69506c0f6d8cb92cb7
https://doi.org/10.1007/3-540-44989-2_110
https://doi.org/10.1007/3-540-44989-2_110
Publikováno v:
Methods and Applications of Artificial Intelligence ISBN: 9783540434726
SETN
SETN
A multi-clustering fusion method is presented based on combining several runs of a clustering algorithm resulting in a common partition. More specifically, the results of several independent runs of the same clustering algorithm are appropriately com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c8612cceaa345840357f14ff1a3a1039
https://doi.org/10.1007/3-540-46014-4_21
https://doi.org/10.1007/3-540-46014-4_21
Publikováno v:
Multiple Classifier Systems ISBN: 9783540422846
Multiple Classifier Systems
Multiple Classifier Systems
It has been shown by several researchers that multiclassifier systems can result in effective solutions to difficult tasks. In this work, we propose a multi-classifier system based on both supervised and unsupervised learning. According to the princi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d95f1d8405a7773a3fa1cfcf0d714e8
https://doi.org/10.1007/3-540-48219-9_20
https://doi.org/10.1007/3-540-48219-9_20
Publikováno v:
Multiple Classifier Systems (9783540422846); 2001, p198-207, 10p
Publikováno v:
International Journal of Neural Systems; Oct2005, Vol. 15 Issue 5, p391-401, 11p, 2 Charts, 12 Graphs
Autor:
Josef Kittler, Fabio Roli
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Su