I'd like to know if it's possible to create a neural network that receive multiple input images (imageInputLayer)
For example a Siamese architecture for computing the disparity (stereo correspondence) out of two image patches. The network input is two images and the output is a scalar that represent the disparity.
Currently matlab supports a single imageInputLayer for each neural network.
I'd like to to classify a 3D object by projecting the 3D object through 3 angles, Therefor converting the problem to classification of 3 images.
I'm trying to create a network that looks like the attached image.
Please let me know what you think and how to work things out with the network input.