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Home/Authors/Arlene John

Arlene John

1 indexed paper

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Publications per year

1
26

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ML×1

Frequent co-authors

Vigneshwar Hariharan1×
Chithra Reghuvaran1×
Nhat Pham1×
Omer Rana1×
Deepu John1×
Ganesh Neelakanta Iyer1×

Research Timeline

2026
EEG-FuseFormer: A Transformer-Driven Feature Fusion Framework for Seizure Onset Prediction

The paper proposes EEG-FuseFormer, a transformer-based framework that fuses features from CNN-LSTM and ResNet-18 to achieve high accuracy in predicting seizure onset from EEG signals.

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Papers

cs.LGRecentJun 1, 2026

EEG-FuseFormer: A Transformer-Driven Feature Fusion Framework for Seizure Onset Prediction

Vigneshwar Hariharan, Chithra Reghuvaran, Arlene John, Nhat Pham +3 more

The paper proposes EEG-FuseFormer, a transformer-based framework that fuses features from CNN-LSTM and ResNet-18 to achieve high accuracy in predicting seizure onset from EEG signals.

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