Learnable Subspace Orthogonal Projection for Semi-supervised Image Classification.
Lijian LiYunhe ZhangAiping HuangPublished in: ACCV (3) (2022)
Keyphrases
- image classification
- orthogonal projection
- semi supervised
- hilbert space
- subspace learning
- sparse coding
- locally linear embedding
- feature extraction
- sparse representation
- semi supervised learning
- manifold learning
- linear subspace
- low dimensional
- image representation
- von neumann
- labeled data
- dimensionality reduction
- pairwise
- unlabeled data
- exact solution
- learning algorithm
- multi view
- image features
- high dimensional data
- active learning
- finite dimensional
- visual words
- scale spaces
- infinite dimensional
- feature space
- principal components
- convex sets
- principal component analysis
- multivariate time series
- supervised learning
- principal components analysis
- reproducing kernel hilbert space
- feature maps
- low rank
- high dimensional
- continuous functions
- linear discriminant analysis
- input data
- face recognition
- computer vision