A Novel Deep Learning Framework by Combination of Subspace-Based Feature Extraction and Convolutional Neural Networks for Hyperspectral Images Classification.
Tayeb AlipourfardHossein ArefiSomayeh MahmoudiPublished in: IGARSS (2018)
Keyphrases
- feature extraction
- hyperspectral images
- deep learning
- pattern recognition
- feature vectors
- feature selection
- hyperspectral
- dimensionality reduction
- feature space
- image processing
- hyperspectral data
- dimension reduction
- machine learning
- unsupervised learning
- high dimensional
- principal component analysis
- video sequences
- weakly supervised
- convolutional neural networks
- principal components
- remote sensing
- high dimensional data
- low dimensional
- feature set
- data points