Handwriting Recognition

The following demo uses a feed forward multi-layer perceptron with 40 hidden units, trained for about 700 epochs using the back-propagation algorithm, with weight momentum.

Draw a roman numeral digit 0 - 9, and it will try and find which digit are you writing!

NOTE:If it doesn't work, try writing it in another style, or try making your digit fatter or thinner or taller or shorter.
Numbers must span about 90% of the height of the box, and 80% of the width of the box!

Example digit:

Downloads


handwriting_MLP_network.nwk - Network Weights Data File
evaluate.cpp - Evaluation Program - Main Source
evaluate.exe - Evaluation Program - Win32 x86 Binary
neural.h - Neural Network MLP Class
train.h - Training Management Functions
neural.cpp - Training Program - Main Source
neural.exe - Training Program - Win32 x86 Binary
optdigits.tra - Training Data Set
optdigits.tes - Testing Data Set

Data set taken from UCI Maching Learning Repository, and originally came from E Alpaydin, C. Kaynak.

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