The spiking neural network (SNN) and convolutional neural network (CNN) both run using python by using an MNIST dataset of hand-drawn images. Among the packages used were torch, torchvision , and spikingjelly for the SNN and NumPy and keras for the CNN.
The intention of this code was to test and compare the efficency of SNNs and CNNs for empirical research purposes. The current README.md file contains basic information about the repository, but it is missing some key elements that would make it more informative and user-friendly. Here are some suggestions to improve it:
The goal of this project is to test and compare the efficiency of SNNs and CNNs for empirical research purposes.
To get started with the project, follow these steps:
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Clone the repository:
git clone https://github.com/RadoKyselak/Neuromorphic_Comp.git cd Neuromorphic_Comp -
Create a virtual environment and activate it:
python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
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Install the required packages:
pip install -r requirements.txt
To run the SNN code:
python run_snn.pyTo run the CNN code:
python run_cnn.pyThis project is licensed under the Apache License. See the LICENSE file for details.
If you have any questions or feedback, please feel free to reach out by opening an issue or contacting the maintainers.