N-Caltech101
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Object Classification | N-Caltech101 | Accuracy87.1 | 37 | |
| Object Detection | N-Caltech101 | mAP0.73 | 19 | |
| Object Recognition | N-Caltech101 | Latency (s)0.0225 | 18 | |
| Event-based camera denoising | N-Caltech101 BA noise 8%, Hot pixel noise 4% | TPR96.3 | 12 | |
| Event-based camera denoising | N-Caltech101 BA noise 10%, Hot pixel noise 2% | TPR96.5 | 12 | |
| Object Recognition | N-Caltech101 (EST) | Accuracy (N-Caltech101 EST)86.6 | 10 | |
| Object recognition | N-Caltech101 1.0 (test) | Top-1 Accuracy96.47 | 9 | |
| Object Recognition | N-CALTECH101 (test) | Accuracy92.3 | 9 | |
| Image Classification | N-Caltech101 | Accuracy92.58 | 7 | |
| Event-based Object Recognition | N-CALTECH101 (test) | Top-1 Accuracy78.5 | 6 | |
| Event-based Image Classification | N-CALTECH101 (test) | Accuracy71.2 | 6 | |
| Event-based Recognition | N-Caltech101 | Top-1 Accuracy70.03 | 5 |
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