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Table 9 Comparison of the accuracy in relation to the state of the art

From: A comparative study of CNN-capsule-net, CNN-transformer encoder, and Traditional machine learning algorithms to classify epileptic seizure

Algorithms

Authors

Multiclass accuracy

Binary accuracy

Time of compilation [Min]

Parameters [millions]

1D-CNN-LSTM

Gaowei Xu et al. [12].

82.00

99.39

266

2.23

CNN+Capsule-Net

Proposed model

87.00

99.92

8

5.04

CNN+Tf

Proposed model

88.00

99.76

25

22.82