37-ACRS_H_1.pdf

URL: http://portal.igg.ac.mn/en/dataset/4e677c91-326b-4dd4-979c-8020ebf07689/resource/ed19b458-39bb-47f5-af3d-30e2258d02c6/download/37-acrs_h_1.pdf

This paper describes different approaches in feature extraction for a hyperspectral image classification. For the actual feature extraction, principal components transformation, band correlation method, average intensity of the visible/infrared ranges and spectral knowledge are used. The output of each of the feature extraction method is used for a classification process. The results are analyzed and compared.

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Data last updated January 29, 2020
Metadata last updated January 29, 2020
Created January 29, 2020
Format application/pdf
License Creative Commons Attribution
createdover 4 years ago
formatPDF
has viewsTrue
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last modifiedover 4 years ago
mimetypeapplication/pdf
on same domainTrue
package id4e677c91-326b-4dd4-979c-8020ebf07689
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size148.9 KiB
stateactive
url typeupload