Interpretable Machine Learning On Cub 200
Métriques
Top 1 Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Top 1 Accuracy | Paper Title | Repository |
|---|---|---|---|
| Q-SENN | 85.9 | Q-SENN: Quantized Self-Explaining Neural Networks | |
| SLDD-Model | 85.7 | Take 5: Interpretable Image Classification with a Handful of Features |
0 of 2 row(s) selected.