Can someone explain to me how each layer in a CNN analyzes a certain feature and how weight is distributed?
Say – we’ve got a trained dataset of mountains and clouds of all different types. Our new input is the (traditional) windows XP homescreen. If say, the first layer detects color, the second layer detects edges and the third detects overall shapes, how would we determine if clouds are present in the picture?
Sorry if this question is also confusing because I’m pretty confused as well 🙂 All help is greatly appreciated, thanks in advance