Age Estimation On Chalearn 2015
Métriques
e-error
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | e-error |
|---|---|
| deep-expectation-of-real-and-apparent-age | 0.264975 |
| metaage-meta-learning-personalized-age | 0.250651 |
| learning-expectation-of-label-distribution | 0.272 |
| moving-window-regression-a-novel-approach-to | - |
| bridgenet-a-continuity-aware-probabilistic | 0.255140 |
| agenet-deeply-learned-regressor-and | 0.270685 |
| deep-label-distribution-learning-with-label | 0.31 |