Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images

The paper presents a study of various approaches to the classification of soil covers based on neural network algorithms using hyperspectral remote and proximal sensing of the Earth. The spectral distributions were recorded in the laboratory using an Offner imaging scanning hyperspectrometer. Spectr...

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Bibliographic Details
Main Authors:	N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer
Format:	Article
Language:	English
Published:	Samara National Research University 2023-10-01
Series:	Компьютерная оптика
Subjects:	hyperspectral images hyperspectral sensing proximal sensing convolutional neural networks spectral-spatial classification soil cartography
Online Access:	https://www.computeroptics.ru/eng/KO/Annot/KO47-5/470514e.html
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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images

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