Zobrazeno 1 - 10
of 482
pro vyhledávání: '"Sankur, B."'
Publikováno v:
IEEE Transactions on Signal Processing, vol. 19, issue 9, 2010, pp. 2357-2368
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmi
Externí odkaz:
http://arxiv.org/abs/1101.1396
In this paper, we propose a method for activity recognition from videos based on sparse local features and hypergraph matching. We benefit from special properties of the temporal domain in the data to derive a sequential and fast graph matching algor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0a29d25b6df18aa84e2ce634eb479e6
http://arxiv.org/abs/1505.00581
http://arxiv.org/abs/1505.00581
Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco, 2013
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::724ba76a5c78e4f5740268124a28c5b8
Autor:
Sankur, B., Sübakan, Yusuf Cem
Publication in the conference proceedings of EUSIPCO, Bucharest, Romania, 2012
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47d71267fe6bed9ea4637c1b7efd5a9c
Publikováno v:
Publons
Scopus-Elsevier
Scopus-Elsevier
Publication in the conference proceedings of EUSIPCO, Barcelona, Spain, 2011
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39a314986e9f82f670bd6b1598530183
Autor:
Ozdemir, Huseyin, Sankur, B.
Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c918c8d47e57b5266d8af217bbe29fe9
Autor:
Ozay, Nedret, Sankur, B.
Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21d075cb1ca63da2139277c496400fe5
Publikováno v:
ISTI Technical reports, 2009
We propose to model the image differentials of astrophysical sources with Student's t-distribution and use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::61571a4b46831c20acd4ecda366e8d23
https://openportal.isti.cnr.it/doc?id=people______::61571a4b46831c20acd4ecda366e8d23
https://openportal.isti.cnr.it/doc?id=people______::61571a4b46831c20acd4ecda366e8d23
Publikováno v:
IEEE 16th International Conference on Image Processing, pp. 2769–2772, Cairo, Egypt, 7-10 November 2009
info:cnr-pdr/source/autori:Kayabol K.; Kuruoglu E. E.; Sankur B.; Salerno E.; Bedini L./congresso_nome:IEEE 16th International Conference on Image Processing/congresso_luogo:Cairo, Egypt/congresso_data:7-10 November 2009/anno:2009/pagina_da:2769/pagina_a:2772/intervallo_pagine:2769–2772
info:cnr-pdr/source/autori:Kayabol K.; Kuruoglu E. E.; Sankur B.; Salerno E.; Bedini L./congresso_nome:IEEE 16th International Conference on Image Processing/congresso_luogo:Cairo, Egypt/congresso_data:7-10 November 2009/anno:2009/pagina_da:2769/pagina_a:2772/intervallo_pagine:2769–2772
We propose an adaptive Monte Carlo Markov Chain (MCMC) simulation for the Bayesian source separation problem and apply it to the unmixing of astrophysical components. In this method, we use the Langevin stochastic equation for transitions, which enab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::53f2337bb3c2bb01aeaf802040a9673b
http://www.cnr.it/prodotto/i/91982
http://www.cnr.it/prodotto/i/91982