ANN_MLP vs DNN

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the ann has only one type of layers -- fully connected ones (think of it as a matrix-multiplication)

while dnns can contain a multitude of other concepts, convolutional layers, pooling, even layers, that are small ann's themselves (like inception)

Right on. Thanks @berak

Is there a standard text for DNN applications?

I have read the Wikipedia article on deep neural networks, and it says that multiple hidden layer ANNs are considered to be deep neural networks. I tried to make a multiple hidden layer ANN using ANN_MLP, and it seems to work (well, no assertions fail nor are exceptions thrown).

const int num_input_neurons = dove.cols;
const int num_output_neurons = 2;
const int num_hidden_neurons = static_cast<int>(sqrtf(image_width*image_height*num_output_neurons));
Mat layersSize = Mat(4, 1, CV_16UC1);
layersSize.row(0) = Scalar(num_input_neurons);
layersSize.row(1) = Scalar(num_hidden_neurons);
layersSize.row(2) = Scalar(num_hidden_neurons);
layersSize.row(3) = Scalar(num_output_neurons);
mlp->setLayerSizes(layersSize);

yes, above should work, but that's probably already the limit, what you can do with it.

and i don't think, there's a standard text for deep learning .. here are some links, i found useful:

http://colah.github.io/posts/2014-07-...

https://cs231n.github.io/

http://www.computervisionblog.com/

http://theorangeduck.com/page/neural-...

http://www.themtank.org/a-year-in-com...

http://karpathy.github.io/2015/05/21/...

https://github.com/Smorodov/Deep-lear....

Thanks @berak !