Keyphrases
Classification Accuracy
16%
Classification Scheme
16%
Collaborative Representation
100%
Compressed Sensing Theory
16%
Computational Complexity
16%
Computational Cost
16%
Discrimination Power
16%
Feature-based
100%
Gabor Features
100%
Gabor Transform
16%
Generalization Ability
16%
High Performance
16%
High-dimensional Data
16%
Hyperspectral
50%
Hyperspectral Image Classification
100%
L0 Norm
16%
L1-norm
16%
L1-norm Minimization
16%
L1-norm Optimization
16%
L2 Norm
33%
Limited Training Data
16%
Linear Combination
16%
Material Feature
16%
Nonparametric
16%
Pattern Classification Problem
16%
Process Optimization
16%
Recent Advances
16%
Representation Error
16%
Representation Method
16%
Robustness to Noise
16%
Sample Space
16%
Sparse Representation Classifier
33%
Sparse Solution
16%
Sparsity
16%
State-of-the-art Techniques
16%
Training Data
16%
Training Samples
16%
Engineering
Classification Accuracy
33%
Classification Scheme
33%
Compressive Sensing
33%
Computational Complexity
33%
Computational Cost
33%
Dimensional Data
33%
Hyperspectral Data
66%
Hyperspectral Imagery
100%
Linear Combination
33%
Pattern Recognition
33%
Recognition Problem
33%
Sample Space
33%
Sparsity
33%
State-of-the-Art Method
33%
Test Sample
66%
Computer Science
Classification Accuracy
16%
Classification Scheme
16%
Collaborative Representation
100%
Compressive Sensing
16%
Computational Complexity
16%
Computational Cost
16%
Gabor feature
100%
Generalization Ability
16%
High Dimensional Data
16%
Hyperspectral Data
33%
Pattern Recognition
16%
Process Optimization
16%
Recognition Problem
16%
Representation Method
16%
Sparse Linear Combination
16%
Sparse Representation
33%
Sparse Solution
16%
Sparsity
16%
Training Data
16%
Training Sample
16%