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Hyperspectral Band Selection via Tensor Low Rankness and Generalized 3DTV †
Katherine Henneberger,
Jing Qin
Mathematics
Center for Computational Sciences
UNITE Research Priority Area
Research output
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Contribution to journal
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Article
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peer-review
1
Scopus citations
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Dive into the research topics of 'Hyperspectral Band Selection via Tensor Low Rankness and Generalized 3DTV †'. Together they form a unique fingerprint.
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Engineering
Computational Efficiency
100%
Numerical Experiment
100%
Spatial Dimension
100%
Dimensionality
100%
Noisy Data
100%
Selection Method
100%
Selection Algorithm
100%
Practical Guideline
100%
Computational Complexity
100%
Total Variation
100%
Alternating Direction Method of Multipliers
100%
Spectral Dimension
100%
Grid Search
100%
Computer Science
Band Selection
100%
Computational Complexity
20%
Data Structure
20%
High Dimensionality
20%
Alternating Direction Method of Multipliers
20%
Computational Efficiency
20%
Total Variation
20%
Selection Method
20%
Memory Consumption
20%
Spectral Dimension
20%
Practical Guideline
20%
Spatial Dimension
20%
Selection Model
20%
Mathematics
Tensor
100%
Total Variation
25%
Data Structure
25%
Numerical Experiment
25%
Alternating Direction Method of Multipliers
25%
Noisy Data
25%
Bayesian Optimization
25%
Grid Search
25%