2022
DOI: 10.21608/ijicis.2022.147175.1198
|View full text |Cite
|
Sign up to set email alerts
|

Hyperspectral Image Analysis Using a Custom Spectral Convolutional Neural Network

Abstract: In recent time, the most applied classification method for hyperspectral images is based on the supervised deep learning approach. The hyperspectral images require special handling while it consists of hundreds of bands / channels. In this article, the experiments are conducted using one of the widespread deep learning models, Convolutional Neural Networks (CNNs), specifically, Csutom Spectral CNN architecture (CSCNN). The introduced network is based on the data reduction and data normalization. It firstly omm… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 8 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?