Exploring Spectral and Spatial Features Using a Hybrid Approach Combining Stacked AutoEncoder and a Novel Convolutional Neural Network for Hyperspectral Image Classification
Author:
Affiliation:
1. Rajshahi University of Engineering & Technology,Department of Computer Science & Engineering,Rajshahi,Bangladesh
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9689773/9689775/09689851.pdf?arnumber=9689851
Reference23 articles.
1. Deep supervised learning for hyperspectral data classification through convolutional neural networks
2. Hyperspectral Classification Via Spatial Context Exploration with Multi-Scale CNN
3. Learning Compact and Discriminative Stacked Autoencoder for Hyperspectral Image Classification
4. Imagenet classification with deep convolutional neural networks;krizhevsky;Advances in neural information processing systems,2012
5. Feature extraction using convolution neural networks (cnn) and deep learning;jogin;2018 3rd IEEE International Conference on Recent Trends in Electronics Information & Communication Technology (RTEICT),2018
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