I am trying to wrap my head around multiple output of neural networks, especially output of CNN in image classification with localization:
Lets say we have CNN with 2 cond layers (conv + pool, conv + pool) and 2 fully-connected (FC) layers. At the end, the last FC layer is connected to softmax layer. The softmax layer will output vector of probabilities of classes (let's say we have 4: dog, cat, car, something else). Now my question is, what is the way to retrieve the location of detected object? I mean the vector $(x,y,width,height)$?
If I understand it correctly, I map another layer to the last FC layer (so the last FC layer is connected to softmax layer, and this layer). However how does it outputs the vector I need? I am really confused about this.