Saliency fusion via sparse and double low rank decomposition.
Junxia LiJian YangChen GongQingshan LiuPublished in: Pattern Recognit. Lett. (2018)
Keyphrases
- low rank
- tensor decomposition
- low rank matrix
- rank minimization
- low rank subspace
- nuclear norm
- low rank matrices
- sparsity constraints
- matrix factorization
- low rank representation
- robust principal component analysis
- group sparsity
- linear combination
- missing data
- convex optimization
- matrix completion
- regularized regression
- singular value decomposition
- kernel matrices
- high order
- matrix decomposition
- high dimensional data
- semi supervised
- low rank approximation
- kernel matrix
- sparse matrix
- saliency detection
- minimization problems
- trace norm
- data matrix
- affinity matrix
- approximation methods
- singular values
- saliency map
- low rank and sparse
- salient object detection
- image processing
- binary matrices
- image denoising
- least squares
- data analysis
- pattern recognition