Research on Iris Feature Extraction and Recognition Technology Based on Deep Learning
, , et
15 mars 2024
À propos de cet article
Publié en ligne: 15 mars 2024
Pages: 35 - 45
DOI: https://doi.org/10.2478/ijanmc-2023-0064
Mots clés
© 2023 Yufei Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Figure. 1.
Figure. 2.
Figure. 3.
Figure. 4.
Figure. 5.
Figure. 6.
Figure. 7.
Figure. 8.
Figure. 9.
Figure. 10.
Figure. 11.
Figure. 12.
Figure. 13.
Figure. 14.
Figure. 15.
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 |