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Is it possible to use deep network designer App to design CNN for image enhancement?

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I have matlab R2020a and I want to use deep network designer to design my own network for image enhancement. However, I found that the available layers and network examples in deep network designer App are for the task of image classification or regression. ( i.e. the network input is an image and the network output is a label not an image). and I want to design and train a network for image enhancement in which that the network recieves image as an input and outputs an image also not a label. Does anyone know is it possible to do that and how?
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Image Analyst
Image Analyst on 4 Jun 2020
You can build your own network from scratch if you want. I believe you just drag and drop components onto the design layout.
ghada sandoub
ghada sandoub on 4 Jun 2020
Edited: ghada sandoub on 4 Jun 2020
I already tried to build the network from the scratch. My network needs only some convolutional layers, and ReLUs. however, I found some limitations in this App like :
(1) I should start the network with imageinput layer with specified input size, However, I want the network to process input image of any size without resizing the input size.
(2) I need the output to be an image not a label. I found all output layers in the deep network designer related to classification or regression in which the output is a label.
for more details: I want to use CNN for image enhancement, there is some stages to do that like: feature extractin, non-linear mapping and reconstraction. the input for the CNN is an image and the output should be the enhanced image. I want to know how to do this in matlab using deep network designer. Any help will be appreciated.

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