Support Vector Machines in Handwritten Digits Classification

I
ISDA
2005
5th International Conference on Intelligent Systems Design and Applications (ISDA'05)
Abstract - Support Vector Machines in Handwritten Digits Classification

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Urszula Markowska-Kaczmar Articles by Pawel Kubacki

5th International Conference on Intelligent Systems Design and Applications (ISDA'05)

Wroclaw, Poland

September 08-September 10

ISBN: 0-7695-2286-6

	ASCII Text	x
	Urszula Markowska-Kaczmar, Pawel Kubacki, "Support Vector Machines in Handwritten Digits Classification," Intelligent Systems Design and Applications, International Conference on, pp. 406-411, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005.

	BibTex	x
	@article{ 10.1109/ISDA.2005.87, author = {Urszula Markowska-Kaczmar and Pawel Kubacki}, title = {Support Vector Machines in Handwritten Digits Classification}, journal ={Intelligent Systems Design and Applications, International Conference on}, volume = {0}, year = {2005}, isbn = {0-7695-2286-6}, pages = {406-411}, doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.87}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Intelligent Systems Design and Applications, International Conference on TI - Support Vector Machines in Handwritten Digits Classification SN - 0-7695-2286-6 SP406 EP411 A1 - Urszula Markowska-Kaczmar, A1 - Pawel Kubacki, PY - 2005 KW - null VL - 0 JA - Intelligent Systems Design and Applications, International Conference on ER -

Urszula Markowska-Kaczmar, Wroclaw University of Technology, Poland

Pawel Kubacki, Wroclaw University of Technology, Poland

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2005.87

In the paper our approach to classify handwritten digits by using Support Vector Machines is described. Because of the unsatisfying, long time of training of SVM we propose to apply k-nearest neighbours algorithm with Manhattan distance to obtain reduced size of training set having a hope that this hybrid method does not make the significantly worse results of recognition. The aim of presented further experiments was to verify this assumption.

Citation:

Urszula Markowska-Kaczmar, Pawel Kubacki, "Support Vector Machines in Handwritten Digits Classification," isda, pp.406-411, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.