Tactile Recognition on Closed-set 36-category tactile dataset 1.0 (test)
99.27AccuracyCWT-ResNet-ML
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CWT-ResNet-MLN-way=5-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 99.27 | 8 | 1,428.3 | |
| CWT-ResNet-MLN-way=5-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 98.95 | — | — | |
| AFO-MLP-MLN-way=5-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 98.82 | 2 | 10,241.72 | |
| AFOP-MLN-way=5-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 98.76 | 2 | 391.04 | |
| AFOP-MLN-way=5-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 98.69 | — | — | |
| CWT-ResNet-MLN-way=12-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 98.55 | — | — | |
| AFO-MLP-MLN-way=5-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 97.99 | — | — | |
| AFOP-MLN-way=12-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 97.63 | — | — | |
| CWT-ResNet-MLN-way=12-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 97.59 | — | — | |
| AFOP-MLN-way=12-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 97.23 | — | — | |
| Direct-Prot-MLN-way=5-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 97.22 | 2 | 545.65 | |
| Direct-Prot-MLN-way=5-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 96.82 | — | — | |
| AFO-MLP-MLN-way=12-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 96.25 | — | — | |
| CWT-ResNet-MLN-way=36-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 96.15 | — | — | |
| AFOP-MLN-way=5-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 96.08 | — | — | |
| CWT-ResNet-MLN-way=5-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 95.67 | — | — | |
| AFO-MLP-MLN-way=12-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 95.56 | — | — | |
| MAMLN-way=5-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 95.37 | 20 | 72.87 | |
| Direct-Prot-MLN-way=12-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 95.2 | — | — | |
| MAMLN-way=5-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 94.88 | — | — | |
| AFOP-MLN-way=10-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 94.69 | — | — | |
| AFOP-MLN-way=36-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 94.56 | — | — | |
| AFOP-MLN-way=12-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 94 | — | — | |
| AFOP-MLN-way=36-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 93.65 | — | — | |
| Direct-Prot-MLN-way=12-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 93.56 | — | — | |
| CWT-ResNet-MLN-way=36-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 93.52 | — | — | |
| AFO-MLP-MLN-way=5-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 93.47 | — | — | |
| MAMLN-way=5-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 93.28 | — | — | |
| CWT-ResNet-MLN-way=10-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 92.47 | — | — | |
| Direct-Prot-MLN-way=5-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 92.05 | — | — | |
| CWT-ResNet-MLN-way=12-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 91.13 | — | — | |
| AFOP-MLN-way=28-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 90.32 | — | — | |
| AFO-MLP-MLN-way=10-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 90.09 | — | — | |
| Direct-Prot-MLN-way=36-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 89.87 | — | — | |
| MAMLN-way=12-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 89.32 | — | — | |
| Direct-Prot-MLN-way=10-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 88.79 | — | — | |
| AFOP-MLN-way=36-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 88.74 | — | — | |
| MAMLN-way=12-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 88.61 | — | — | |
| Direct-Prot-MLN-way=36-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 87.89 | — | — | |
| AFO-MLP-MLN-way=12-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 87.82 | — | — | |
| MAMLN-way=10-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 86.7 | — | — | |
| AFO-MLP-MLN-way=36-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 86.22 | — | — | |
| Direct-Prot-MLN-way=12-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 86.18 | — | — | |
| CWT-ResNet-MLN-way=28-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 86.18 | — | — | |
| AFO-MLP-MLN-way=36-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 85.78 | — | — | |
| MAMLN-way=12-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 84.38 | — | — | |
| CWT-ResNet-MLN-way=36-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 84.24 | — | — | |
| Direct-Prot-MLN-way=28-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 80.92 | — | — | |
| Direct-Prot-MLN-way=36-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 78.47 | — | — | |
| AFO-MLP-MLN-way=28-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 75.79 | — | — | |
| MAMLN-way=28-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 73.99 | — | — | |
| BiLSTMN-way=5-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 73.59 | — | — | |
| CNNN-way=5-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 71.78 | — | — | |
| MAMLN-way=36-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 70.77 | — | — | |
| CNNN-way=5-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 70.72 | — | — | |
| BiLSTMN-way=5-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 70.43 | — | 14,495.07 | |
| AFO-MLP-MLN-way=36-way, K-shot=1-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 69.64 | — | — | |
| BiLSTMN-way=5-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 68.85 | — | — | |
| CNNN-way=5-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 68.16 | — | 1,643.25 | |
| MAMLN-way=36-way, K-shot=5-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 68.06 | — | — | |
| CNNN-way=36-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 66.96 | — | — | |
| MAMLN-way=36-way, K-shot=3-shot, Learning Paradigm=Meta-learning (episodic)2026.03 | 63.89 | — | — | |
| CNNN-way=12-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 60.94 | — | — | |
| BiLSTMN-way=12-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 59.6 | — | — | |
| BiLSTMN-way=12-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 55.63 | — | — | |
| CNNN-way=12-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 45.68 | — | — | |
| CNNN-way=36-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 45.19 | — | — | |
| BiLSTMN-way=36-way, K-shot=5-shot, Learning Paradigm=DL without Meta-learning2026.03 | 44.26 | — | — | |
| BiLSTMN-way=10-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 44.02 | — | — | |
| CNNN-way=10-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 41.48 | — | — | |
| BiLSTMN-way=12-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 39.2 | — | — | |
| CNNN-way=12-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 35.57 | — | — | |
| BiLSTMN-way=36-way, K-shot=3-shot, Learning Paradigm=DL without Meta-learning2026.03 | 32.85 | — | — | |
| BiLSTMN-way=36-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 21.71 | — | — | |
| BiLSTMN-way=28-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 16.78 | — | — | |
| CNNN-way=28-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 14.86 | — | — | |
| CNNN-way=36-way, K-shot=1-shot, Learning Paradigm=DL without Meta-learning2026.03 | 14.14 | — | — |