Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Shadrin, Dmitrii"'
The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote sensing imagery provides vital information for the landcover classification, especially concerning the vegetation assessment. Despite the usefulness of NIR, comm
Externí odkaz:
http://arxiv.org/abs/2106.07020
Autor:
Illarionova, Svetlana, Nesteruk, Sergey, Shadrin, Dmitrii, Ignatiev, Vladimir, Pukalchik, Mariia, Oseledets, Ivan
Publikováno v:
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021, pp. 1659-1668
Today deep convolutional neural networks (CNNs) push the limits for most computer vision problems, define trends, and set state-of-the-art results. In remote sensing tasks such as object detection and semantic segmentation, CNNs reach the SotA perfor
Externí odkaz:
http://arxiv.org/abs/2105.05516
Large datasets' availability is catalyzing a rapid expansion of deep learning in general and computer vision in particular. At the same time, in many domains, a sufficient amount of training data is lacking, which may become an obstacle to the practi
Externí odkaz:
http://arxiv.org/abs/2102.12295
Autor:
Shadrin, Dmitrii, Pukalchik, Mariia, Uryasheva, Anastasia, Tsykunov, Evgeny, Yashin, Grigoriy, Rodichenko, Nikita, Tsetserukou, Dzmitry
Plant diseases can lead to dramatic losses in yield and quality of food, becoming a problem of high priority for farmers. Apple scab, moniliasis, and powdery mildew are the most significant apple tree diseases worldwide and may cause between 50% and
Externí odkaz:
http://arxiv.org/abs/2004.02325
Autor:
Shadrin, Dmitrii1 (AUTHOR), Illarionova, Svetlana1 (AUTHOR) s.Illarionova@skoltech.ru, Gubanov, Fedor1,2 (AUTHOR), Evteeva, Ksenia1 (AUTHOR), Mironenko, Maksim1 (AUTHOR), Levchunets, Ivan3 (AUTHOR), Belousov, Roman3 (AUTHOR), Burnaev, Evgeny1 (AUTHOR)
Publikováno v:
Scientific Reports. 1/31/2024, Vol. 14 Issue 1, p1-17. 17p.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
E3S Web of Conferences, Vol 542, p 04003 (2024)
Currently, remote sensing techniques assist in various environmental applications and facilitate observation and spatial analysis. Machine learning algorithms allow researchers to find dependencies in satellite data and vegetation cover properties. O
Externí odkaz:
https://doaj.org/article/dfd867d13d9a40af87f9370665a171cc
Autor:
Uryasheva, Anastasia, Kalashnikova, Aleksandra, Shadrin, Dmitrii, Evteeva, Ksenia, Moskovtsev, Evgeny, Rodichenko, Nikita
Publikováno v:
In Computers and Electronics in Agriculture October 2022 201
Autor:
Shadrin, Dmitrii1 (AUTHOR), Menshchikov, Alexander1 (AUTHOR), Nikitin, Artem1 (AUTHOR), Ovchinnikov, George1 (AUTHOR), Volohina, Vera2 (AUTHOR), Nesteruk, Sergey1 (AUTHOR), Pukalchik, Mariia3 (AUTHOR), Fedorov, Maxim1 (AUTHOR), Somov, Andrey1 (AUTHOR) a.somov@skoltech.ru
Publikováno v:
Eng. Sep2023, Vol. 4 Issue 3, p2055-2074. 20p.