This is a 3-layer SNN for MNIST. This code is based on spikingjelly, you need to download spikingjelly. SNN2.py is used to train the network and save the Loss and accuracy files. Before running SNN2.py, you need to copy class LIFNode2 to neuron.py (package that comes with spikingjelly). load_npy.py is used to download the saved accuracy and Loss files. load_model.py is used to download the trained model and generate hotmap images (classification results)
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billyuanpku96/SNN-for-sensory-neuron
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This is a 3-layer SNN for MNIST
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