Both CNNs and SNNs have an input layer and an output layer with one or more hidden layers in between. So fundamentally they're no different. The real problem is they both don't give prediction accuracy to be reliably used in real world. It's nice to see in academia they're using for research but very few companies risk it to use in real world. We are not there yet. and it's a very slow process can take decades to get there to get an acceptable level of predictions and accuracy.
Ultra-low power neuromorphic execution of convolutional neural networks, page-39
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