Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Eremeev Vladimir Alekseevich"'
Autor:
Odinokikh Gleb Andreevich, Mikhail Vladimirovich Korobkin, Michael N. Rychagov, Eremeev Vladimir Alekseevich, Gnatyuk Vitaly Sergeevich, Alexey Mikhailovich Fartukov
Publikováno v:
Pattern Recognition and Image Analysis. 28:516-524
In spite of a fact that many standalone iris recognition solutions are successfully implemented and deployed around the world, development of a reliable iris recognition solution capable to provide high recognition performance (both in biometric qual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88e82ebb88c72f30e30599f4e3bc1aa2
https://doi.org/10.1134/s105466181803015x
https://doi.org/10.1134/s105466181803015x
Autor:
Lee Heejun, Alexey Mikhailovich Fartukov, Alexey Bronislavovich Danilevich, Odinokikh Gleb Andreevich, Kwang-Hyun Lee, Sergey Zavalishin, Eremeev Vladimir Alekseevich, Dae-Kyu Shin, Yoo Juwoan, Solomatin Ivan Andreevich, Xenya Petrova, Gnatyuk Vitaly Sergeevich
Publikováno v:
2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI).
In this paper, we propose a novel algorithm for automatic camera parameter adjustment, which is exploited for getting the correct image exposure required for iris recognition. We use two-step processing, where the first step adjusts the camera parame
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95d19ac8adebd1161f2c2a6a07800555
https://doi.org/10.1109/ecai46879.2019.9042077
https://doi.org/10.1109/ecai46879.2019.9042077
Autor:
Odinokikh Gleb Andreevich, Eremeev Vladimir Alekseevich, Gnatyuk Vitaly Sergeevich, Mikhail Vladimirovich Korobkin
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030353995
IDP
IDP
Information about eyelid position in an image is used during iris recognition for eyelid and eyelash noise removal, iris image quality estimation and other purposes. Eyelid detection is usually performed after iris-sclera boundary localization which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b40297b4480b7b1315e86474f9a0c59
https://doi.org/10.1007/978-3-030-35400-8_10
https://doi.org/10.1007/978-3-030-35400-8_10
Publikováno v:
Doklady Earth Sciences. 413:393-396
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::233c8626340bb95a9f24000ea0474754
https://doi.org/10.1134/s1028334x07030166
https://doi.org/10.1134/s1028334x07030166
Publikováno v:
Geophysical Research Letters. 32
[1] A 26-year (1979–2004) observational record of January multiyear sea ice distributions, derived from neural network analysis of SMMR-SSM/I passive microwave satellite data, reveals dense and persistent cover in the central Arctic basin surrounde
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76d99edd4b86bc2e9ac1e3b8d1060fd4
https://doi.org/10.1029/2005gl022395
https://doi.org/10.1029/2005gl022395
Autor:
Eremeev Vladimir Alekseevich, David C. Douglas, I. N. Mordvintsev, G. I. Belchansky, I. V. Alpatsky, N. G. Platonov
Publikováno v:
IGARSS
Three ice-type classification methods utilizing SSM/I passive microwave data were compared. Each applied a multilayer perceptron (MLP) neural network (NN) with OKEAN (radar and passive microwave) sea-ice learning data, a different learning algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f69614b8a26c98efb3623d1e649a7be
https://doi.org/10.1109/igarss.2003.1294432
https://doi.org/10.1109/igarss.2003.1294432