Semi-Supervised Deep Learning Using Pseudo Labels for Hyperspectral Image Classification

Deep learning has gained popularity in a variety of computer vision tasks. Recently, it has also been successfully applied for hyperspectral image classification tasks. Training deep neural networks, such as a convolutional neural network for classification requires a large number of labeled samples...

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Bibliographic Details
Published in:	IEEE transactions on image processing 2018-03, Vol.27 (3), p.1259-1270
Main Authors:	Hao Wu, Prasad, Saurabh
Format:	Article
Language:	English
Subjects:	Artificial neural networks Bayesian analysis Classification Clustering Computer vision constrained Dirichlet process mixture model Convolutional recurrent neural networks Deep learning Dirichlet problem Feature extraction Hyperspectral imaging Image classification Inference Labels Machine learning Neural networks pseudo labels Recurrent neural networks Remote sensing Semi-supervised learning Spatial data Training
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