Seizure Type Classification on IIIC Seizure
57.75Balanced AccuracyTFM-Tokenizer
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| TFM-TokenizerModel Size=1.9M, Training Setting=Single Dataset Setting2025.02 | 57.75 | 49.85 | 58.47 | |
| Vanilla BIOTModel Size=3.2M, Training Setting=Single Dataset Setting2025.02 | 57.62 | 49.32 | 57.73 | |
| TFM-Tokenizer †Model Size=1.9M, Training Setting=With Multiple Dataset Pretraining2025.02 | 57.47 | 49.79 | 57.97 | |
| CBraMod†Model Size=4M, Training Setting=With Multiple Dataset Pretraining2025.02 | 55.66 | 47.92 | 57.43 | |
| ContraWRModel Size=1.6M, Training Setting=Single Dataset Setting2025.02 | 54.21 | 45.49 | 53.87 | |
| CNN-TransformerModel Size=3.2M, Training Setting=Single Dataset Setting2025.02 | 53.95 | 45 | 54.13 | |
| FFCLModel Size=2.4M, Training Setting=Single Dataset Setting2025.02 | 53.09 | 44.12 | 53.15 | |
| ST-TransformerModel Size=3.5M, Training Setting=Single Dataset Setting2025.02 | 50.93 | 42.17 | 52.17 | |
| SPaRCNetModel Size=0.79M, Training Setting=Single Dataset Setting2025.02 | 50.11 | 41.15 | 49.96 | |
| LaBraM-Base*Model Size=5.8M, Training Setting=Single Dataset Setting2025.02 | 47.36 | 37.16 | 47.65 | |
| LaBraM-Base†Model Size=5.8M, Training Setting=With Multiple Dataset Pretraining2025.02 | 47.36 | 36.58 | 47.08 | |
| EEGPTModel Size=4.7M, Training Setting=With Multiple Dataset Pretraining2025.02 | 45.45 | 35.02 | 45.59 | |
| BIOT*Model Size=3.2M, Training Setting=Single Dataset Setting2025.02 | 44.58 | 34.18 | 45.11 | |
| BIOTModel Size=3.2M, Training Setting=With Multiple Dataset Pretraining2025.02 | 44.14 | 33.62 | 44.83 |