A Comparative Analysis of Tensor Decomposition Models Using Hyper Spectral Image
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Summary
The results have proved that Block Term Decomposition (BTD) is the best tensor model for decomposing the hyper spectral image in to resultant factor.
- Type
- preprint
- Published
- 2015-03-23
- Cited by
- 4
- References
- 27
- Access
- Open access
- OpenAlex
- https://openalex.org/W307245813
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17351208
Keywords
Tensor (intrinsic definition), Decomposition, Block (permutation group theory), Computer science, Set (abstract data type)
References
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- Handwritten digit classification using higher order singular value decomposition
- Tensor Completion for Estimating Missing Values in Visual Data
- Classification of hyperspectral images by tensor modeling and additive morphological decomposition
- Face recognition in hyperspectral images
- Sulfates in Martian Layered Terrains: The OMEGA/Mars Express View
- Hyperspectral imaging: a novel approach for microscopic analysis.
- Temporal Analysis of Semantic Graphs Using ASALSAN
- Commodity cluster-based parallel processing of hyperspectral imagery
- Unsupervised Multiway Data Analysis: A Literature Survey
- Selecting among three-mode principal component models of different types and complexities: a numerical convex hull based method.
- ResearchArticle Canonical Decomposition of Ictal Scalp EEG and Accurate Source Localisation: Principles and Simulation Study
- The Expression of a Tensor or a Polyadic as a Sum of Products
- Multiple Invariants and Generalized Rank of a P‐Way Matrix or Tensor
Cited by
- Anomaly detecting in hyperspectral imageries based on tensor decomposition with spectral and spatial partitioning
- Application of hyperspectral image anomaly detection algorithm for Internet of things
- Application and Analysis of Hyperspectal Imaging
- Evolutionary Tensor Train Decomposition for Hyper-Spectral Remote Sensing Images
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