Low-Rank Linear Embedding for Image Recognition

Keyphrases

• Benchmark Dataset 50%
• Character Image 50%
• Face Image 50%
• Feature Extraction 100%
• Feature Selection 50%
• Guaranteed Convergence 50%
• Image Recognition 100%
• Iterative Algorithm 50%
• Jointly Sparse 50%
• L2,1-norm 50%
• L2,1-norm Regularization 50%
• Latent Relations 50%
• Linear Embedding 100%
• Locality Preserving Projection 100%
• Loss Function 50%
• Low-rank 100%
• Low-rank Constraint 50%
• Optimization Problem 50%
• Recognition Efficiency 50%
• Reconstruction Error 50%
• Regression Matrix 100%
• Regression Model 50%
• Regularization Term 50%
• Sparse Regression 50%

Computer Science

• Experimental Result 50%
• Feature Extraction 100%
• Feature Selection 50%
• Iterative Algorithm 50%
• locality preserving projection 100%
• Modified Version 50%
• Optimization Problem 50%
• Reconstruction Error 50%
• Regularization Term 50%