langfengQ / MLF-DSResNet

This is the implementation of MLF & spiking DS-ResNet

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Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks

IJCAI 2022

This repository contains Python implementation of MLF & spiking DS-ResNet.

1. Publication

If you find this repository useful, please consider citing the following paper:

@inproceedings{lang2022multi,
  title     = {Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks},
  author    = {Feng, Lang and Liu, Qianhui and Tang, Huajin and Ma, De and Pan, Gang},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  pages     = {2471--2477},
  year      = {2022},
  doi       = {10.24963/ijcai.2022/343},
  url       = {https://doi.org/10.24963/ijcai.2022/343},
}

2. Datasets

3. Dependencies:

  • python 3.7.10
  • numpy 1.19.5
  • torch 1.9.0+cu111
  • torchvision 0.10.0+cu111
  • tensorboardX 2.4
  • h5py 3.3.0

4. Preprocessing

DVS-gesture and CIFAR10-DVS need to be pre-processed. The syntax is as follow,

python DVS_CIFAR10_preprocess.py
python DVS_Gesture_preprocess.py

5. Traning

To train a new model, the basic syntax is like:

python train_for_cifar10.py
python train_for_gesture.py
python train_for_dvscifar10.py

About

This is the implementation of MLF & spiking DS-ResNet

License:MIT License


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