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

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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???

Answers (1)

Mahesh Taparia
Mahesh Taparia on 8 Mar 2022
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
Nagwa megahed on 8 Mar 2022
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
Mahesh Taparia on 10 Mar 2022
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.

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