Gesture Recognition On Dvs128 Gesture
Métriques
Accuracy (%)
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy (%) |
|---|---|
| sequence-approximation-using-feedforward | 98.0 |
| alert-transformer-bridging-asynchronous-and | 94.1 |
| scalable-event-by-event-processing-of | 97.7 |
| online-training-through-time-for-spiking | 96.88 |
| a-synapse-threshold-synergistic-learning | 97.22 |
| hardware-software-co-design-with-adc-less-in | 95.15 |
| building-temporal-kernels-with-orthogonal | 100.00 |
| convolutional-spiking-neural-networks-for | 96.7 |
| comparing-snns-and-rnns-on-neuromorphic | 86.81 |
| egru-event-based-gru-for-activity-sparse | 97.8 |
| alert-transformer-bridging-asynchronous-and | 96.2 |
| sequence-approximation-using-feedforward | 96.6 |
| temporal-binary-representation-for-event | 97.73 |
| s-tllr-stdp-inspired-temporal-local-learning | 97.72 |