Study of Spatial–Spectral Feature Extraction Frameworks With 3-D Convolutional Neural Network for Robust Hyperspectral Imagery Classification

Study of Spatial–Spectral Feature Extraction Frameworks With 3-D Convolutional Neural Network for Robust Hyperspectral Imagery Classification

Advances in hyperspectral remote sensing have instigated multitude of applications for better understanding of our planet through remote data acquisition and observation of natural phenomena such as weather monitoring and prediction to include tornado, wild fires, global warming, etc. For this, data...

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Bibliographic Details
Main Authors: Bishwas Praveen, Vineetha Menon
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
3-D convolutional neural network (3-D CNN)
deep learning
dimensionality reduction (DR)
feature extraction
Gabor filtering
Gaussian filtering
Online Access:https://ieeexplore.ieee.org/document/9305246/

Internet

https://ieeexplore.ieee.org/document/9305246/

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