Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Ilze Andersone"'
Publikováno v:
Complex Systems Informatics and Modeling Quarterly, Vol 0, Iss 32, Pp 44-54 (2022)
The presented work proposes a practical approach to bird weight data processing and augmentation to enable production outcome forecast model training, which contributes to higher productivity. We suggest using the parametrized model, where parameter
Externí odkaz:
https://doaj.org/article/cd6801c346354bdfb06d9bc65dc00555
Autor:
Giulia Bassanese, Tanja Wlodkowski, Aude Servais, Laurence Heidet, Dario Roccatello, Francesco Emma, Elena Levtchenko, Gema Ariceta, Justine Bacchetta, Giovambattista Capasso, Augustina Jankauskiene, Marius Miglinas, Pietro Manuel Ferraro, Giovanni Montini, Jun Oh, Stephane Decramer, Tanja Kersnik Levart, Jack Wetzels, Elisabeth Cornelissen, Olivier Devuyst, Aleksandra Zurowska, Lars Pape, Anja Buescher, Dieter Haffner, Natasa Marcun Varda, Gian Marco Ghiggeri, Giuseppe Remuzzi, Martin Konrad, Germana Longo, Detlef Bockenhauer, Atif Awan, Ilze Andersone, Jaap W. Groothoff, Franz Schaefer
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 16, Iss 1, Pp 1-15 (2021)
Abstract Background The European Rare Kidney Disease Reference Network (ERKNet) recently established ERKReg, a Web-based registry for all patients with rare kidney diseases. The main objectives of this core registry are to generate epidemiological in
Externí odkaz:
https://doaj.org/article/298d7b2d56344d9ab3fa1ca68f07142f
Autor:
Ilze Andersone
Publikováno v:
Robotics, Vol 8, Iss 3, p 74 (2019)
Multi-robot mapping and environment modeling have several advantages that makeit an attractive alternative to the mapping with a single robot: faster exploration, higherfault tolerance, richer data due to different sensors being used by different sys
Externí odkaz:
https://doaj.org/article/85a4295229b940d4a246d2484f43f7e7
Publikováno v:
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
Publikováno v:
2022 7th International Conference on Machine Learning Technologies (ICMLT).
Publikováno v:
2022 7th International Conference on Machine Learning Technologies (ICMLT).
Publikováno v:
IFIP Advances in Information and Communication Technology ISBN: 9783031083365
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::182e913bce1a40307d6cfa8fc37e37af
https://doi.org/10.1007/978-3-031-08337-2_37
https://doi.org/10.1007/978-3-031-08337-2_37
Autor:
Pietro Manuel Ferraro, Elena Levtchenko, Tanja Kersnik Levart, Jaap W. Groothoff, Olivier Devuyst, Giovanni Montini, Anja Buescher, Dario Roccatello, Justine Bacchetta, Francesco Emma, Jun Oh, Dieter Haffner, Elisabeth A.M. Cornelissen, Tanja Wlodkowski, Martin Konrad, Jack F.M. Wetzels, Natasa Marcun Varda, Gema Ariceta, Detlef Bockenhauer, Aleksandra Zurowska, Germana Longo, Augustina Jankauskiene, Aude Servais, Giuseppe Remuzzi, Ilze Andersone, Franz Schaefer, Laurence Heidet, Lars Pape, Stéphane Decramer, Giovambattista Capasso, Marius Miglinas, Gian Marco Ghiggeri, Giulia Bassanese, Atif Awan
Publikováno v:
Orphanet journal of rare diseases, London : BioMed Central Ltd., 2021, vol.16, no. 1, p. 1844-1859
Orphanet journal of rare diseases, 16(1):251. BioMed Central
Orphanet Journal of Rare Diseases, 16
Scientia
Orphanet Journal of Rare Diseases
Orphanet Journal of Rare Diseases, Vol 16, Iss 1, Pp 1-15 (2021)
Orphanet Journal of Rare Diseases, Vol. 16, no.1, p. 251 (2021)
Orphanet Journal of Rare Diseases, 16, 1
Orphanet journal of rare diseases, 16(1):251. BioMed Central
Orphanet Journal of Rare Diseases, 16
Scientia
Orphanet Journal of Rare Diseases
Orphanet Journal of Rare Diseases, Vol 16, Iss 1, Pp 1-15 (2021)
Orphanet Journal of Rare Diseases, Vol. 16, no.1, p. 251 (2021)
Orphanet Journal of Rare Diseases, 16, 1
Epidemiologia; Nefrologia pediàtrica; Registre Epidemiología; Nefrología pediátrica; Registro Epidemiology; Pediatric nephrology; Registry Background The European Rare Kidney Disease Reference Network (ERKNet) recently established ERKReg, a Web-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f580ddf5b1808b33370d6fb1bbd3079
https://www.ncbi.nlm.nih.gov/pubmed/34078418
https://www.ncbi.nlm.nih.gov/pubmed/34078418
Autor:
Ilze Andersone
Publikováno v:
ICAART (1)
Autor:
Ilze Andersone
Publikováno v:
Procedia Computer Science. 104:362-368
This paper proposes a probabilistic robotic mapping approach to merge ultrasonic distance readings by modelling them as Gaussian random variables and using scan matching to reduce uncertainty in mapping process. To account for the high angular uncert