1. Example: ZIP Code Recognition Classification of handwritten numerals

2. Example: ZIP Code Recognition Net-1: no hidden layer, equivalent to multinomial logistic regression Net-2: one hidden layer, 12 hidden units fully connected Net-3: two hidden layers locally connected Net-4: two hidden layers, locally connected with weight sharing Net-5: two hidden layers, locally connected, two levels of weight sharing

3. Example: ZIP Code Recognition Net-3 use local connectivity –Each hidden unit is connected to only a small patch of units in the layer below Net-4 and Net-5: local connectivity, shared weights –Convolutional networks –Weights shared by all units in a feature map Design of Net- 5 –Motivated by that features of handwriting style appear in more than one part of a digit NNs are not a fully automatic tool –Subject matter knowledge