Interpretable Machine Learning On Cub 200
Metriken
Top 1 Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | 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 |
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