Table 8 SOTA method comparison on PUT, PolyU, and biocop DATASETS.
From: PatternFusion: a hybrid model for pattern recognition in time-series data using ensemble learning
Model | Dataset | EER (%) | FAR (%) | FRR (%) |
|---|---|---|---|---|
VGGFace2 + IrisCode | PUT | 2.3 | 2.5 | 2.2 |
PolyU | 2.7 | 3.0 | 2.4 | |
BioCop | 3.1 | 3.5 | 2.8 | |
CNN-LSTM Fusion | PUT | 2.1 | 2.4 | 2.0 |
PolyU | 2.5 | 2.8 | 2.3 | |
BioCop | 2.9 | 3.3 | 2.7 | |
Multi-stream transformers | PUT | 1.8 | 2.0 | 1.7 |
PolyU | 2.0 | 2.2 | 1.9 | |
BioCop | 2.5 | 2.8 | 2.3 | |
PatternFusion (proposed) | PUT | 1.2 | 1.5 | 1.1 |
PolyU | 1.5 | 1.7 | 1.3 | |
BioCop | 1.8 | 2.0 | 1.6 |
