Multi-class Classification on Office+Caltech cross-domain scenarios (DeCAF6 features)
85.72Average AccuracyDAM
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| DAMFeatures=Raw2015.10 | 85.72 | — | — | — | — | |
| L-SVMFeatures=Raw2015.10 | 82.66 | — | — | — | — | |
| 1-NNFeatures=Raw2015.10 | 70.38 | — | — | — | — | |
| LRE-SVMInput Features=DeCAF62015.10 | 0.86 | 0.9187 | 0.8638 | 0.8459 | 0.8117 | |
| SCAInput Features=DeCAF62015.10 | 0.8512 | 0.9238 | 0.8673 | 0.8584 | 0.7554 | |
| UMLInput Features=DeCAF62015.10 | 0.8436 | 0.9102 | 0.8459 | 0.8229 | 0.7954 | |
| L-SVMInput Features=DeCAF62015.10 | 0.8402 | 0.9134 | 0.8495 | 0.8186 | 0.7794 | |
| Undo-BiasInput Features=DeCAF62015.10 | 0.8185 | 0.9098 | 0.8595 | 0.8049 | 0.6998 | |
| DICAInput Features=DeCAF62015.10 | 0.8102 | 0.904 | 0.8433 | 0.7965 | 0.6973 | |
| USCAInput Features=DeCAF62015.10 | 0.7911 | 0.8946 | 0.7715 | 0.781 | 0.7174 | |
| KPCAInput Features=DeCAF62015.10 | 0.7771 | 0.8914 | 0.7587 | 0.7899 | 0.6884 | |
| 1NNInput Features=DeCAF62015.10 | 0.7228 | 0.8539 | 0.7373 | 0.6792 | 0.6709 |