|OCR with Multi-Layer Perceptrons|
This applet illustrates some pattern recognition capabilities of the multi-layer perceptrons with an Optical Character Recognition (OCR) application. A database is used to learn handwritten digits ranging from 0 to 9. Then, the user can draw digits himself, and try to make the perceptron recognize them.
The original applet was written by Olivier Michel.
A database of bitmaps is used to learn to recognize handwritten figures between 0 and 9. Each bitmap is a 15x20 binary map representing an handwritten digit. 100 samples (10 for each digit) were drawn by hand, with a computer mouse. The input layer of the neural network fcontains 80 neurons representing a 8x10 matrix corresponding to a subsampling of the actual sample matrix. For each input unit, a preprocessing module computes a value equal to the average of the four corresponding input pixels of the input matrix. The output layer is made up of 10 units, each one indicating a symbolic value for the digit recognized.