Click here to Skip to main content
11,935,345 members (60,200 online)
Click here to Skip to main content


529 bookmarked

Neural Network for Recognition of Handwritten Digits

, 5 Dec 2006
A convolutional neural network achieves 99.26% accuracy on a modified NIST database of hand-written digits.
// stdafx.cpp : source file that includes just the standard includes
//	MNist.pch will be the pre-compiled header
//	stdafx.obj will contain the pre-compiled type information

#include "stdafx.h"

By viewing downloads associated with this article you agree to the Terms of Service and the article's licence.

If a file you wish to view isn't highlighted, and is a text file (not binary), please let us know and we'll add colourisation support for it.


This article has no explicit license attached to it but may contain usage terms in the article text or the download files themselves. If in doubt please contact the author via the discussion board below.

A list of licenses authors might use can be found here


About the Author

Mike O'Neill
United States United States
Mike O'Neill is a patent attorney in Southern California, where he specializes in computer and software-related patents. He programs as a hobby, and in a vain attempt to keep up with and understand the technology of his clients.

You may also be interested in...

| Advertise | Privacy | Terms of Use | Mobile
Web04 | 2.8.151126.1 | Last Updated 5 Dec 2006
Article Copyright 2006 by Mike O'Neill
Everything else Copyright © CodeProject, 1999-2015
Layout: fixed | fluid