Multi-layer neural networks for handwritten digit recognition

This report documents the underlining theories and neural network that lead to the development of handwritten digit recognition architecture that are capable of recognizing handwritten digit with recognition accuracy of up to 76%.

Saved in:

Bibliographic Details
Main Author:	Kyaw, Zin Min.
Other Authors:	Saratchandran, Paramasivan
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/4543
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-4543
record_format	dspace
spelling	sg-ntu-dr.10356-45432023-07-04T15:59:15Z Multi-layer neural networks for handwritten digit recognition Kyaw, Zin Min. Saratchandran, Paramasivan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This report documents the underlining theories and neural network that lead to the development of handwritten digit recognition architecture that are capable of recognizing handwritten digit with recognition accuracy of up to 76%. Master of Science (Computer Control and Automation) 2008-09-17T09:53:51Z 2008-09-17T09:53:51Z 2003 2003 Thesis http://hdl.handle.net/10356/4543 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Kyaw, Zin Min. Multi-layer neural networks for handwritten digit recognition
description	This report documents the underlining theories and neural network that lead to the development of handwritten digit recognition architecture that are capable of recognizing handwritten digit with recognition accuracy of up to 76%.
author2	Saratchandran, Paramasivan
author_facet	Saratchandran, Paramasivan Kyaw, Zin Min.
format	Theses and Dissertations
author	Kyaw, Zin Min.
author_sort	Kyaw, Zin Min.
title	Multi-layer neural networks for handwritten digit recognition
title_short	Multi-layer neural networks for handwritten digit recognition
title_full	Multi-layer neural networks for handwritten digit recognition
title_fullStr	Multi-layer neural networks for handwritten digit recognition
title_full_unstemmed	Multi-layer neural networks for handwritten digit recognition
title_sort	multi-layer neural networks for handwritten digit recognition
publishDate	2008
url	http://hdl.handle.net/10356/4543
_version_	1772828436805451776

Multi-layer neural networks for handwritten digit recognition

Similar Items