Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Mochalova Anastasia"'
Autor:
Pal, Sumanta Kumar, Albiges, Laurence, Tomczak, Piotr, Suárez, Cristina, Voss, Martin H, de Velasco, Guillermo, Chahoud, Jad, Mochalova, Anastasia, Procopio, Giuseppe, Mahammedi, Hakim, Zengerling, Friedemann, Kim, Chan, Osawa, Takahiro, Angel, Martín, Gupta, Suyasha, Khan, Omara, Bergthold, Guillaume, Liu, Bo, Kalaitzidou, Melania, Huseni, Mahrukh, Scheffold, Christian, Powles, Thomas, Choueiri, Toni K *
Publikováno v:
In The Lancet 15-21 July 2023 402(10397):185-195
Akademický článek
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Autor:
Neal, Joel, Pavlakis, Nick, Kim, Sang-We, Goto, Yasushi, Lim, Sun Min, Mountzios, Giannis, Fountzilas, Elena, Mochalova, Anastasia, Christoph, Daniel C., Bearz, Alessandra, Quantin, Xavier, Palmero, Ramon, Antic, Vladan, Chun, Elaine, Edubilli, Tirupathi Rao, Lin, Ya-Chen, Huseni, Mahrukh, Ballinger, Marcus, Graupner, Vilma, Curran, Dominic
Publikováno v:
Journal of Clinical Oncology; 7/10/2024, Vol. 42 Issue 20, p2393-2403, 16p
Akademický článek
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Autor:
Mochalov Vladimir, Mochalova Anastasia
Publikováno v:
E3S Web of Conferences, Vol 196, p 03002 (2020)
In order to improve the quality of recognition of ionograms, the use of general knowledge about the reference marking of ionograms at various points of installation of ionosondes of the same type is considered. On the basis of reference markings from
Externí odkaz:
https://doaj.org/article/9e23498f17894058a0ad19668c442945
Autor:
Mochalov Vladimir, Mochalova Anastasia
Publikováno v:
E3S Web of Conferences, Vol 196, p 02007 (2020)
In this paper, the previously obtained results on recognition of ionograms using deep learning are expanded to predict the parameters of the ionosphere. After the ionospheric parameters have been identified on the ionogram using deep learning in real
Externí odkaz:
https://doaj.org/article/e5c6b089d0cd4b7e9b88557a3052bef6
Publikováno v:
In Electronic Commerce Research and Applications July-August 2014 13(4):283-294
Autor:
Mochalov Vladimir, Mochalova Anastasia
Publikováno v:
E3S Web of Conferences, Vol 127, p 01004 (2019)
Based on a new developed author’s method for recognition traces of reflections from different layers of the ionosphere in ionograms, the ionosphere parameters are extracted. The method is based on the use of deep neural networks (DNN). The rules fo
Externí odkaz:
https://doaj.org/article/22d7e2e8605d4e5f8ef2e3de77c7ae6d
Autor:
Mochalov Vladimir, Mochalova Anastasia
Publikováno v:
E3S Web of Conferences, Vol 127, p 02024 (2019)
When we analyze geophysical data, the task of searching for structures by their samples and mathematical models often appears. We propose to use deep neural networks (DNN) to search and detect the forms of geophysical structures. At the same time, bo
Externí odkaz:
https://doaj.org/article/c62df846d37745c6b8bbb7e655066e32
Autor:
Mochalov Vladimir, Mochalova Anastasia
Publikováno v:
E3S Web of Conferences, Vol 62, p 02001 (2018)
Algorithms for streaming whistler recognition are offered. Different stages of algorithms are considered. The developed algorithms are used on a mini-computer software and hardware complexes for monitoring very low-frequency electromagnetic radiation
Externí odkaz:
https://doaj.org/article/ddd05ef4ef2f496e9a08168bd299c191