A novel attempt has been made in this paper to diagnose epilepsy from EEG signal using ensemble learning approach.
Higher Order Spectra features are used for classifying normal and ictal class using Support Vector Machine with Radial basis function as kernel and non linear�...
The proposed approach is validated on a public benchmark dataset to compare it with previous studies. Results: The results indicate that the combined use of�...
Sep 8, 2023 � Our work proposes a novel approach for classifying epileptic EEG signals by combining CNN with LSTM network within a bidirectional recurrent�...
Missing: ensemble | Show results with:ensemble
Jan 31, 2023 � We present a new method using data mining and machine learning techniques to diagnose epileptic seizures automatically.
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In this research, we propose a deep learning based ensemble learning method to predict epileptic seizures. In the proposed method, EEG signals are preprocessed�...
Jun 3, 2023 � The Epileptic Seizure Recognition Data Set is a collection of EEG recordings used to recognize epileptic seizures. The dataset is available on�...
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension�...
The proposed system for automatic epilepsy detection using EEG brain signals based on deep learning is shown in Fig. 1. It consists of three main modules�...
Automated epilepsy seizure detection from EEG signal based on hybrid CNN and LSTM model � Classification of Ictal and Preictal Seizure using EEG Signals based on�...