Classification On N Cars
Metriken
Accuracy (%)
Architecture
Params (M)
Representation
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | Accuracy (%) | Architecture | Params (M) | Representation | Paper Title | Repository |
|---|---|---|---|---|---|---|
| Spiking DenseNet121-24 | 90.4 | SNN | 3.93 | VoxelCube | Object Detection with Spiking Neural Networks on Automotive Event Data | |
| MEM | 98.55 | Transformer | - | Event Histogram | Masked Event Modeling: Self-Supervised Pretraining for Event Cameras | |
| Spiking MobileNet-64 | 91.7 | SNN | 18.81 | VoxelCube | Object Detection with Spiking Neural Networks on Automotive Event Data | |
| ResNet34 + EST | 92.5 | CNN | 21.8 | EST | End-to-End Learning of Representations for Asynchronous Event-Based Data | |
| GET | 96.7 | Transformer | 4.5 | Token | GET: Group Event Transformer for Event-Based Vision | - |
| Spiking VGG-11 | 92.4 | SNN | 9.23 | VoxelCube | Object Detection with Spiking Neural Networks on Automotive Event Data |
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