Spectral-spatial neural network classification of hyperspectral vegetation images. Issue 1 (1st February 2023)

• Record Type: Journal Article
• Authors: Podlipnov, V V; Firsov, N A; Ivliev, N A; Mashkov, S V; Ishkin, P A; Skidanov, R V; Nikonorov, A V
• Is Part Of: IOP conference series. Volume 1138:Issue 1(2023)
• Publication Date: 2023-02-01
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/1138/1/012040
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: The paper presents the results of a study of the method of classification of vegetation types based on hyperspectral survey data. A hyperspectrometer based on the Offner scheme was used as a shooting equipment. The spatial-spectral architecture of a convolutional neural network is used as a classifier. The experiments performed show the effectiveness of the proposed approach for the classification of vegetation types.