In our experiments, the experimental subset contains 1,552 images selected from the GT database and the FERET databases. | ☑ The name, source, and compositions of data |
The large-scale database contains 93,638 images captured from 9,668 palms of 4,834 individuals, in which 4–10 images are collected for each palm. | ☑ The source and compositions of data |
Consequently, both of the two experimental subsets contain 1,200 samples for training and 1,200 samples for testing. | ☑ Data compositions and application |
In order to show the robustness over short noisy intervals and satisfy the two defined semantics R1 and R2, we generate two completely separated clusters, C1 and C2, using two disjoint interval sequences, Q1 and Q2, and add the synthetically generated short noisy intervals marked in red. Each group contains 10 subjects. | ☒ Algorithm description |
| ☒ Experiment participants |
The average training time of the repeated random sub-sampling validation is 1.83 × 30 = 54.9 s, and that of the CBE cross-validation is 1.84 × 5 = 9.2 s. | ☒ Experiment process |