Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Mátyás Brendel"'
Autor:
László Orzó, Ákos Zarándy, Viktor Gál, Csaba Rekeczky, J. Hámori, P.L. Venetianer, Tamás Roska, Dávid Bálya, ZS Borostyánkői, J. Takács, Zoltán Vidnyánszky, László Négyessy, K. Lotz, Mátyás Brendel, István Petrás
Publikováno v:
International Journal of Bifurcation and Chaos. 14:551-584
In this paper we demonstrate the potential of the cellular nonlinear/neural network paradigm (CNN) that of the analogic cellular computer architecture (called CNN Universal Machine — CNN-UM) in modeling different parts and aspects of the nervous sy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a8a8ad2eabd5d6d69b7f4ac34966327
https://doi.org/10.1142/s0218127404009545
https://doi.org/10.1142/s0218127404009545
Publikováno v:
Neural Processing Letters. 16:111-120
Single-layer, continuous-time cellular neural/nonlinear networks (CNN) are considered with linear templates. The networks are programmed by the template-parameters. A fundamental question in template training or adaptation is the gradient computation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::228e560d4dea6f988b4df38df2cd51f2
https://doi.org/10.1023/a:1019933009505
https://doi.org/10.1023/a:1019933009505
Autor:
Marc Schoenauer, Mátyás Brendel
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642355325
Artificial Evolution
Artificial Evolution
Learn-and-Optimize (LaO) is a generic surrogate based method for parameter tuning combining learning and optimization. In this paper LaO is used to tune Divide-and-Evolve (DaE), an Evolutionary Algorithm for AI Planning. The LaO framework makes it po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af7de7a77664282612bf13408578ad75
https://doi.org/10.1007/978-3-642-35533-2_13
https://doi.org/10.1007/978-3-642-35533-2_13
Autor:
Marc Schoenauer, Mátyás Brendel
Publikováno v:
GECCO (Companion)
Learn-and-Optimize (LaO) is a generic surrogate based method for parameter tuning combining learning and optimization. In this paper LaO is used to tune Divide-and-Evolve (DaE), an Evolutionary Algorithm for AI Planning. The LaO framework makes it po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81b918832384f9bd8cf9d25191489342
https://doi.org/10.1145/2001858.2002053
https://doi.org/10.1145/2001858.2002053
Publikováno v:
Interspeech 2010.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a724561703089cd4c17bac7c6f4824d1
https://doi.org/10.21437/interspeech.2010-365
https://doi.org/10.21437/interspeech.2010-365
Autor:
András A. Benczúr, Dávid Siklósi, Zsolt Fekete, Bálint Daróczy, Mátyás Brendel, Simon Rácz, Attila Pereszlényi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642044465
CLEF
CLEF
We describe our image processing system used in the Image-CLEF 2008 Photo Retrieval and Visual Concept Detection tasks. Our method consists of image segmentation followed by feature generation over the segments based on color, shape and texture. In t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07e02ae401f93c0217009a0fca2eaca9
https://doi.org/10.1007/978-3-642-04447-2_81
https://doi.org/10.1007/978-3-642-04447-2_81
Autor:
Károly Csalogány, Mátyás Brendel, András A. Benczúr, Dávid Siklósi, István Bíró, Bálint Daróczy
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540857594
CLEF
CLEF
We describe our approach to the ImageCLEFphoto 2007 task. The novelty of our method consists of biclustering image segments and annotation words. Given the query words, it is possible to select the image segment clusters that have strongest cooccurre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1aef013fab4fe13c7bfae66661950faa
https://doi.org/10.1007/978-3-540-85760-0_64
https://doi.org/10.1007/978-3-540-85760-0_64
Publikováno v:
Neural Processing Letters. Oct2002, Vol. 16 Issue 2, p111-120. 10p.
Autor:
Carlos Arturo Hernández Gracidas, András A. Benczúr, Heidy Marisol Marin Castro, Thomas Deselaers, Hermann Ney, Nicu Sebe, Hugo Jair Escalante Balderas, Allan Hanbury, Mátyás Brendel, Lei Wu, Ville Viitaniemi, Steven C. H. Hoi, Bálint Daróczy, Theo Gevers, Mingjing Li, Xiaoguang Rui, Julian Stöttinger, Jorma Laaksonen
Publikováno v:
Scopus-Elsevier
Lecture Notes in Computer Science ISBN: 9783540857594
CLEF (Working Notes)
Lecture Notes in Computer Science ISBN: 9783540857594
CLEF (Working Notes)
We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results. The task was based on the widely used PASCAL object recognition data to train object recognitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06fbf2eb0e9c68a1bdf7ed5bf84e00ea
http://www.scopus.com/inward/record.url?eid=2-s2.0-84921989910&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84921989910&partnerID=MN8TOARS
Conference
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