how can i input two inputs to the deep network, one from the imageinputlayer and the other from featureinputlayer

how can i input the images and the extracted features by one of the algorithms to a deep network

this example shows how can i build the structure of the network with an input layer and feature input layer

but how i can train the network with the two inputs???

[yanqi liu]

what is two inputs mean? two dimension or two variable？

[Nagwa megahed]

two variables ( one is an image datastore and the other is an a table (or array ) with set of features that represent each image)

Answer 1

[Mahesh Taparia]

Hi

You can refer to this example which shows how to combine image and features and then pass it to a CNN. It create a dlnet object which you can train it using custom training loop. For more information, you can refer to this documentation. Hope it will help!

[Nagwa megahed]

Dear sir, thanx for your answer

but i already build the network and combined the input layer with a feature input layer but i ask how can i train the network with two inputs , to train a network you should determine a single input , this input may be an image datastore or image features

my question is how to combine two inputs(image+features) in a single input or if there is another way to choose two inputs for the network

[Mahesh Taparia]

Hi

You can concatenate the image and features in the channels. For example if you have images of size MxNxZ and features of size MxNxK, then concatenate into mxnx(Z+K) size and pass in to network.