Hi,
I have a probably convolution or correlation layer type question.
Imagine a bay window with 3 panes. In front of these window panes from a good distance are lamps positioned that the emitted light is perpendicular to the particular window pane. These light rays are converging on the back wall of the room in a small area.
The question is, if someone makes an image of the light on the wall can a neural network separate where portions of the lights were coming from? Lamps are the same and they are from the same distance from their particular window pane.
My guess is is that somehow the different directions - 45, 90, 135 degrees - has to be picked out, but how?
