In Lesson 7, we see how to add non-spatial meta features to a ConvNet by concatenating them in at the penultimate (conv) layer before feeding them into a dense layer. What about FCN’s where the task is segmentation or per-pixel / per-voxel labeling? If we have useful meta data such as voltage, or altitude, or mph, or some other equivalent scalar that we we’d like to add into the network, how can this be accomplished?
So far, my only thought is to simply encode the data into a w*h image, where every pixel value is equal to whatever single data feature I’d like to add in and then concatenate this in as a channel: e.g. suppose my last conv layer’s input looks like : (None, 5, 256, 256), merge in the fature so that the input is (None, 6, 256, 256) then proceed as normal. However that seems like a very suboptimal and hacky way to go about doing things, since I’d be adding the scalar in 256**2 times.