- https://doi.org/10.1109/icais56108.2023.10073767
EEG Signal Classification using Convolutional Neural Network
- Feb 2, 2023
- Sharmiladevi D +3 more
Abstract
The purpose of this study is to offer a basic Convolutional Neural Network (CNN) software for classifying epileptic seizures. The recognition of the Electroencephalography (EEG) signal and its distinctive features are required for the diagnosis of epileptic seizures. As a result, it requires a mechanism for recognising and categorising epileptic seizures. As part of a neural network, deep learning is used .CNN has shown excellent performance in image classification and pattern identification. This study utilizes the Hanning window FFT analyser and CNN ConvNet to categorize epileptic seizures. To transform the time-frequency domain of the EEG signal data, this transform produces an image that may be classified into five properties.
- # Convolutional Neural Network
- # Performance In Image Classification
- # Epileptic Seizures
- # Excellent Performance In Classification
- # Pattern Identification
- # Image Classification
- # Diagnosis Of Seizures
- # Deep Learning
- # Distinctive Features
- # Neural Network Software
