Protection and Inheritance Strategy of She Traditional Sports Skills Based on Pattern Recognition
21 mars 2025
À propos de cet article
Publié en ligne: 21 mars 2025
Reçu: 06 nov. 2024
Accepté: 13 févr. 2025
DOI: https://doi.org/10.2478/amns-2025-0660
Mots clés
© 2025 Hui Lan, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Comparison of accuracy of the classification data set of the method
| Categories | ST-GCN | 2s-AGCN | DGNN | FenceNet | DLSTM-GCN |
|---|---|---|---|---|---|
| SL-R | 0.38 | 0.58 | 0.45 | 0.72 | 0.81 |
| SL-L | 0.53 | 0.7 | 0.54 | 0.75 | 0.84 |
| SJ-R | 0.38 | 0.39 | 0.2 | 0.2 | 0.82 |
| SJ-L | 0.68 | 0.77 | 0.58 | 0.79 | 0.89 |
| SW-R | 0.44 | 0.6 | 0.79 | 0.66 | 0.85 |
| SW-L | 0.63 | 0.77 | 0.82 | 0.71 | 0.97 |
| FH-R | 0.38 | 0.58 | 0.72 | 0.87 | 0.96 |
| FH-L | 0.55 | 0.89 | 0.83 | 0.76 | 0.88 |
| UC-R | 0.44 | 0.83 | 0.71 | 0.77 | 0.76 |
| UC-L | 0.37 | 0.55 | 0.64 | 0.77 | 0.97 |
Other algorithms compare results
| Model name | Accuracy rate(%) |
|---|---|
| Lie Group | 52.5 |
| ARRN-LSTM | 83.6 |
| 3scale ResNet152 | 87.7 |
| ST-GCN | 81.5 |
| Pb-GCN | 89.2 |
| DGNN | 91.2 |
| DLSTM-GCN | 90.1 |
Comparison of experimental accuracy of action classification data set
| Categories | ST-GCN | 2s-AGCN | DGNN | FenceNet | DLSTM-GCN |
|---|---|---|---|---|---|
| SL-R | 0.38 | 0.58 | 0.45 | 0.72 | 0.71 |
| SL-L | SL-R | 0.12 | 0.41 | 0.68 | 0.39 |
| SJ-R | SL-L | 0.53 | 0.8 | 0.87 | 0.83 |
| SJ-L | SJ-R | 0.88 | 0.89 | 0.87 | 0.87 |
| SW-R | SJ-L | 0.78 | 0.89 | 0.87 | 0.87 |
| SW-L | SW-R | 0.46 | 0.54 | 0.29 | 0.74 |
| FH-R | SW-L | 0.66 | 0.85 | 0.78 | 0.83 |
| FH-L | FH-R | 0.45 | 0.75 | 0.68 | 0.68 |
| UC-R | FH-L | 0.42 | 0.73 | 0.52 | 0.71 |
| UC-L | UC-R | 0.24 | 0.5 | 0.62 | 0.87 |
| Top 1(%) | 67.75 | 84.57 | 76.67 | 82.76 | 93.45 |
| Top 5(%) | 97 | 100 | 98.15 | 99.51 | 100 |
Comparison of experimental results based on action capture
| Model name | Top 1(%) | Top 5(%) |
|---|---|---|
| ST-GCN | 52.11 | 95.76 |
| 2s-AGCN | 53.47 | 94.21 |
| DLSTM-GCN | 63.55 | 98.76 |
The accuracy of various interpolation algorithms is compared
| Interpolation algorithm | Mean error | Error mean square root | ||
|---|---|---|---|---|
| k=2 | k=5 | k=2 | k=5 | |
| 2 times neville | 0.0781 | 0.4612 | 0.1338 | 0.6353 |
| 4 times neville | 0.0413 | 0.3184 | 0.0689 | 0.4474 |
| 8 times neville | 0.0391 | 0.3011 | 0.0628 | 0.4123 |
| Linear interpolation | 0.0781 | 8.0278 | 0.1338 | 9.7477 |
