Standard
Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. / Valery, Grishkin; Evgeniy, Zhivulin; Anastasiia, Khokhriakova.
Computational Science and Its Applications – ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII. ред. / O Gervasi; B Murgante; S Misra; C Garau; Blecic; D Taniar; BO Apduhan; AMAC Rocha; E Tarantino; CM Torre. Springer Nature, 2021. стр. 406-416 (Lecture Notes in Computer Science; Том 12956).
Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Harvard
Valery, G, Evgeniy, Z & Anastasiia, K 2021,
Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. в O Gervasi, B Murgante, S Misra, C Garau, Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino & CM Torre (ред.),
Computational Science and Its Applications – ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII. Lecture Notes in Computer Science, Том. 12956, Springer Nature, стр. 406-416, 21st International Conference on Computational Science and Its Applications, ICCSA 2021, Virtual, Online, Италия,
13/09/21.
https://doi.org/10.1007/978-3-030-87010-2_30
APA
Valery, G., Evgeniy, Z., & Anastasiia, K. (2021).
Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. в O. Gervasi, B. Murgante, S. Misra, C. Garau, Blecic, D. Taniar, BO. Apduhan, AMAC. Rocha, E. Tarantino, & CM. Torre (Ред.),
Computational Science and Its Applications – ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII (стр. 406-416). (Lecture Notes in Computer Science; Том 12956). Springer Nature.
https://doi.org/10.1007/978-3-030-87010-2_30
Vancouver
Valery G, Evgeniy Z, Anastasiia K.
Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. в Gervasi O, Murgante B, Misra S, Garau C, Blecic, Taniar D, Apduhan BO, Rocha AMAC, Tarantino E, Torre CM, Редакторы, Computational Science and Its Applications – ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII. Springer Nature. 2021. стр. 406-416. (Lecture Notes in Computer Science).
https://doi.org/10.1007/978-3-030-87010-2_30
Author
Valery, Grishkin ; Evgeniy, Zhivulin ; Anastasiia, Khokhriakova. /
Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. Computational Science and Its Applications – ICCSA 2021: 21st International Conference, Cagliari, Italy, September 13–16, 2021, Proceedings, Part VIII. Редактор / O Gervasi ; B Murgante ; S Misra ; C Garau ; Blecic ; D Taniar ; BO Apduhan ; AMAC Rocha ; E Tarantino ; CM Torre. Springer Nature, 2021. стр. 406-416 (Lecture Notes in Computer Science).
BibTeX
@inproceedings{27a7771112834fe6801eaf3022a581db,
title = "Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands",
abstract = "Currently, there is significant progress in the interpretation of remote images of the earth{\textquoteright}s surface using various recognition systems. To train these systems, large labeled datasets are required. The creation of such datasets is carried out by experts and is quite a time-consuming task. This paper proposes a method for creating specialized datasets for their use in monitoring the state of agricultural lands undergoing degradation. The method allows you to automate the process of creating such datasets The datasets are generated from freely available data obtained by the Sentinel satellites as part of the European Copernicus space program. The method is based on the processing of the results of the preliminary classification of images of the earth{\textquoteright}s cover, previously produced by the Sentinel Hub service.",
keywords = "Multispectral images, Remote sensing, Satellite image segmentation, Scene classification, Training dataset, BENCHMARK",
author = "Grishkin Valery and Zhivulin Evgeniy and Khokhriakova Anastasiia",
note = "Valery G., Evgeniy Z., Anastasiia K. (2021) Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science, vol 12956. Springer, Cham. https://proxy.library.spbu.ru:2060/10.1007/978-3-030-87010-2_30; 21st International Conference on Computational Science and Its Applications, ICCSA 2021, ICCSA 2021 ; Conference date: 13-09-2021 Through 16-09-2021",
year = "2021",
doi = "10.1007/978-3-030-87010-2_30",
language = "English",
isbn = "9783030870096",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "406--416",
editor = "O Gervasi and B Murgante and S Misra and C Garau and Blecic and D Taniar and BO Apduhan and AMAC Rocha and E Tarantino and CM Torre",
booktitle = "Computational Science and Its Applications – ICCSA 2021",
address = "Germany",
}
RIS
TY - GEN
T1 - Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands
AU - Valery, Grishkin
AU - Evgeniy, Zhivulin
AU - Anastasiia, Khokhriakova
N1 - Valery G., Evgeniy Z., Anastasiia K. (2021) Creation of Specialized Datasets for Satellite Monitoring of the State of Agricultural Lands. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science, vol 12956. Springer, Cham. https://proxy.library.spbu.ru:2060/10.1007/978-3-030-87010-2_30
PY - 2021
Y1 - 2021
N2 - Currently, there is significant progress in the interpretation of remote images of the earth’s surface using various recognition systems. To train these systems, large labeled datasets are required. The creation of such datasets is carried out by experts and is quite a time-consuming task. This paper proposes a method for creating specialized datasets for their use in monitoring the state of agricultural lands undergoing degradation. The method allows you to automate the process of creating such datasets The datasets are generated from freely available data obtained by the Sentinel satellites as part of the European Copernicus space program. The method is based on the processing of the results of the preliminary classification of images of the earth’s cover, previously produced by the Sentinel Hub service.
AB - Currently, there is significant progress in the interpretation of remote images of the earth’s surface using various recognition systems. To train these systems, large labeled datasets are required. The creation of such datasets is carried out by experts and is quite a time-consuming task. This paper proposes a method for creating specialized datasets for their use in monitoring the state of agricultural lands undergoing degradation. The method allows you to automate the process of creating such datasets The datasets are generated from freely available data obtained by the Sentinel satellites as part of the European Copernicus space program. The method is based on the processing of the results of the preliminary classification of images of the earth’s cover, previously produced by the Sentinel Hub service.
KW - Multispectral images
KW - Remote sensing
KW - Satellite image segmentation
KW - Scene classification
KW - Training dataset
KW - BENCHMARK
UR - http://www.scopus.com/inward/record.url?scp=85115733587&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/73836fe6-8ef0-3fa7-8f0b-3e0d90d81c7f/
U2 - 10.1007/978-3-030-87010-2_30
DO - 10.1007/978-3-030-87010-2_30
M3 - Conference contribution
AN - SCOPUS:85115733587
SN - 9783030870096
T3 - Lecture Notes in Computer Science
SP - 406
EP - 416
BT - Computational Science and Its Applications – ICCSA 2021
A2 - Gervasi, O
A2 - Murgante, B
A2 - Misra, S
A2 - Garau, C
A2 - Blecic, null
A2 - Taniar, D
A2 - Apduhan, BO
A2 - Rocha, AMAC
A2 - Tarantino, E
A2 - Torre, CM
PB - Springer Nature
T2 - 21st International Conference on Computational Science and Its Applications, ICCSA 2021
Y2 - 13 September 2021 through 16 September 2021
ER -
