Analyzing hyperspectral and hypertemporal data by decoupling feature redundancy and feature relevance

Keyphrases

• Hyperspectral 100%
• Feature Relevance 100%
• Feature Decoupling 100%
• Feature Redundancy 100%
• Hyper-temporal 100%
• Sequential Feature Selection 66%
• Classification Problem 33%
• Support Vector Machine 33%
• Computationally Expensive 33%
• Redundancy 33%
• Classification Task 33%
• Feature Selection Methods 33%
• Unsupervised Clustering 33%
• Earth Observation Data 33%
• Information Redundancy 33%
• Supervised Learning Algorithms 33%
• Spectral Cluster 33%
• Comparable Accuracy 33%
• Feature Ranking 33%
• Forward Selection 33%
• Neighborhood Features 33%
• Correlated Features 33%
• Cluster Representative 33%
• Temporal Cluster 33%
• Regression Task 33%
• Temporal Segment 33%

Computer Science

• Feature Selection 100%
• Feature Extraction 100%
• Supervised Learning 50%
• Support Vector Machine 50%
• Information Redundancy 50%
• Regression Task 50%
• Cluster Representative 50%
• Learning Algorithm 50%
• Classification Task 50%
• Classification Problem 50%
• Forward Selection 50%
• Unsupervised Clustering 50%

Biochemistry, Genetics and Molecular Biology

• Feature Extraction 100%
• Support Vector Machine 50%