I have some images with a csv file containing some additional information about them / features and I want to do a binary classification.
My idea is to use a CNN with the image (already working) and use an other CNN with Tabular for the csv file and merge them at some layer to make a unique output.
My question is can I make a learner with two inputs?
Or should I just make my one input as a concatenation of image+tabular info and slice it as my first layer and run two branches until the merge?
Is a even possible or should I stay with two separate models and do some kind of weighted voting on the prediction ?
Thank you !