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When reading about convolutional neural networks (CNNs), I often come across a special notation used in the community and in scientific papers, describing the architecture of the network in terms of layers. However, I was not able to find a paper or resource describing this notation in detail.

Could someone explain to me the details or point to where it is described or "standardized"?

Examples:

`input−100C3−MP2−200C2−MP2−300C2−MP2−400C2−MP2−500C2−output`

(source)`input−(300nC2−300nC2−MP2)_5−C2−C1−output`

(source)

A good guess seems that *x*`C`

*y* are convolution layers (*x* is number of filters? *y* is one side of square kernel?). `MP`

*z* is max-pooling layer (pool size *z*×*z*?).

But instead of guessing, I would love to have a reference (which I could possibly also reference in a paper).

Thanks, this is definitely helpful, especially the reference! There is one line missing from the original paper, proposed a change. Thanks again – Czechnology – 2018-01-31T12:42:20.697