Research on Iris Feature Extraction and Recognition Technology Based on Deep Learning
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15 mar 2024
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Publicado en línea: 15 mar 2024
Páginas: 35 - 45
DOI: https://doi.org/10.2478/ijanmc-2023-0064
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© 2023 Yufei Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Analysis of experimental data
| Test Methods | Training Set | Test Set | Number Of Correct Identifications | Recognition Rate % (Crr) |
|---|---|---|---|---|
| CNN | 400 | 60 | 56 | 92 |
| LMD | 400 | 60 | 47 | 78 |
Comparison of the content of the two datasets
| Training Set | Test Set | Training Set | Test Set | |
|---|---|---|---|---|
| Number of categories | 50 | 8 | 45 | 6 |
| Number of images/classes | 20 | 20 | 10 | 10 |
| Total number of images | 342 | 58 | 342 | 58 |