This project aims to detect schizophrenia using wavelet transform and a ResNet-18 based classification model. The utilization of wavelet transform allows for a detailed analysis of Electroencephalogram (EEG) data, providing valuable insights into the components of brain signals.
- Schizophrenia detection through EEG data.
- Wavelet transform for feature extraction.
- ResNet-18 for classification.
- GradCAM for explainability on wavelet scalograms.
- Clone the repository:
git clone https://github.com/Rish-01/Schizo-xai.git cd Schizo-xai - Install Dependencies:
pip install -r requirements.txt
.
├── EEG_data
├── image_dir
│ ├── healthy
│ └── schizophrenic
├── model_checkpoints
├── requirements.txt
└── Schizo.ipynb