Siamese Network-Based Feature Transformation for Improved Automated Epileptic Seizure Detection

Table 7

Comparison of the proposed method with the state-of-the-art methods for cases 1, 9, and 11 using University of Bonn database in terms of classification accuracy (%).

Authors	Case 1	Case 9	Case 11
Kaya [12]	100	—	95.7
Tuncer [13]	100	—	98.67
Mamli [14]	100	97.38	99.26
Aydemir, [15]	100	—	99.67
Wu [38]	100	99.6	99.4
Jiang [11]	100	99.6	99.88
Jiang [10]	100	99.33	99.33
Proposed method	100	99.69	99.95