backpropagation convolutional neural network Yann LeCun backpropagation recognizing handwritten ZIP codes Yann LeCun training Neocognitron
In 1988, Wei Zhang et al. applied the backpropagation algorithm 
to a convolutional neural network (a simplified Neocognitron with convolutional interconnections between the image feature layers and the last fully connected layer) for alphabet recognition. They also proposed an implementation of the CNN with an optical computing system. 
In 1989, Yann LeCun et al. applied backpropagation to a CNN with the purpose of recognizing handwritten ZIP codes on mail. While the algorithm worked, training required 3 days. Subsequently, Wei Zhang, et al. modified their model by removing the last fully connected layer and applied it for medical image object segmentation in 1991 and breast cancer detection in mammograms in 1994. LeNet-5 (1998), a 7-level CNN by Yann LeCun et al., that classifies digits, was applied by several banks to recognize hand-written numbers on checks  digitized in 32x32 pixel images.
