Combine customized neural network with CNN

As I found we can customized each layers in a CNN, and we can also do customizing our own neural network by "net=network" and set properties of "net". But can those class of CNN layer be used in a general neural network? I want to combine the output of two CNN as two channel of 'image' and do CNN on this new 'image'

Answer 1

[Chaitral Date]

Regarding your first question, No, you shouldn't be able to use CNN layer classes in a general neural network. It'll still take on somewhat a similar form to a CNN. There is some flexibility, but a lot of limitations at the same time.

Regarding your second question, The two channels portion is very unclear. What is the output that you are currently getting from the two CNN?

[MatlabUserN]

Basically, the question is how to cascade two CNN is series or parallel to generate single prediction in matlab

[Jason Vann]

This is exactly the kind of feature I would like to see. I would like to develop a network with parallel CNNs and connected at the end with a fully connected and classification layer. Looking at the R2017b pre-release, there is a custom layer capability which may help address this issue, but it would be a very convoluted work-around.

[Alexander Tarroni]

I am also trying to fuse two pre-trained VGG16 models with a single softmax layer at their output, with two inputs taking separate data. It seems you can't make convolutional layers in the custom neural network functions, is there any way to fuse layers from different convnets otherwise?