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Table 2 Experimental results for S2S and S2R in the second session based on different pre-trained models

From: An evaluation of transfer learning models in EEG-based authentication

Model

Comparison of performance metrics (Averaged% ± Standard deviation)

Session 2: S2S

Session 2: S2R

Acc.

Pre.

Sens.

Spec.

F1

Acc.

Pre.

Sens.

Spec.

F1

GoogLeNet

99.19 ± 0.53

99.21 ± 0.53

99.17 ± 0.54

99.96 ± 0.02

99.18 ± 0.55

99.42 ± 0.23

99.42 ± 0.22

99.39 ± 0.24

99.96 ± 0.01

99.40 ± 0.24

Inception-V3

99.84 ± 0.23

99.85 ± 0.21

99.84 ± 0.23

99.98 ± 0.01

99.84 ± 0.23

99.95 ± 0.08

99.95 ± 0.28

99.94 ± 0.08

99.98 ± 0.003

99.94 ± 0.08

ResNet-50

99.88 ± 0.01

99.90 ± 0.002

99.90 ± 0.01

99.99 ± 0.02

99.89 ± 0.001

99.89 ± 0.002

99.90 ± 0.01

99.44 ± 0.63

99.99 ± 0.02

99.89 ± 0.002

ResNet-101

99.68 ± 0.15

99.69 ± 0.14

99.66 ± 0.14

99.97 ± 0.01

99.67 ± 0.14

99.79 ± 0.30

99.78 ± 0.31

99.78 ± 0.31

99.98 ± 0.01

99.78 ± 0.31

EfficientNet-B0

99.89 ± 0.16

99.87 ± 0.019

99.86 ± 0.20

99.98 ± 0.01

99.86 ± 0.19

99.84 ± 0.23

99.84 ± 0.23

99.83 ± 0.24

99.98 ± 0.01

99.83 ± 0.24

DenseNet-201

99.98 ± 0.01

99.98 ± 0.02

99.98 ± 0.02

99.99 ± 0.01

99.99 ± 0.01

99.89 ± 0.01

99.90 ± 0.01

99.88 ± 0.01

99.99 ± 0.02

99.89 ± 0.01

  1. The bold values indicate the highest accuracy