Research map / Label-efficient and robust learning / Recognition and long-tail
Multi-Kernel Low-Rank Dictionary Pair Learning for Multiple Features Based Image Classification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add low-rank regularization on the analysis dictionary (ablation) | MKLDPL · Flowers17 | accuracy (%): 90.31 -> 91.69 | Helped |
| add low-rank regularization on the analysis dictionary (ablation) | MKLDPL · Flowers102 | accuracy (%): 78.88 -> 80.17 | Helped |
| add low-rank regularization on the analysis dictionary (ablation) | MKLDPL · Caltech101 | accuracy (%): 85.65 -> 86.81 | Helped |
| use analysis-synthesis dictionary pair instead of synthesis dictionary only (MKDPL vs DMKDL) (ablation) | multi-kernel dictionary learning · Flowers17 | accuracy (%): 88.13 -> 90.31 | Helped |
| use analysis-synthesis dictionary pair instead of synthesis dictionary only (MKDPL vs DMKDL) (ablation) | multi-kernel dictionary learning · Caltech101 | accuracy (%): 82.66 -> 85.65 | Helped |
| use MKLDPL instead of DMKDL under 30% image noise | multi-kernel DL · Caltech101 noise 30% | accuracy (%): 65.16 -> 72.13 | Helped |
| vary lambda in [0.1,1] | MKLDPL · Flowers17 | accuracy | No clear effect |
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