Probabilistic learning vector quantization on manifold of symmetric positive definite matrices.
Fengzhen TangHaifeng FengPeter TinoBailu SiDaxiong JiPublished in: Neural Networks (2021)
Keyphrases
- learning vector quantization
- symmetric positive definite matrices
- valued data
- dictionary learning
- matrix valued
- sparse coding
- riemannian metric
- riemannian manifolds
- self organizing maps
- generative model
- log euclidean
- sparse representation
- neural network
- probabilistic model
- dt mri
- covariance matrices
- tensor field
- euclidean space
- vector valued
- natural images
- feature space
- dw mri
- computer vision
- manifold learning
- unsupervised learning
- low dimensional
- pattern recognition