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On the Importance of Accurate Weak Classifier Learning for Boosted weak Classifiers

Date

Authors

Overett, Gary

Petersson, Lars

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

Recent work [1], has shown that improving model learning for weak classifiers can yield significant gains in the overall accuracy of a boosted classifier. However, most published classifier boosting research relies only on rudimentary learning techniques

Keywords

Keywords: Classifiers; Education; Intelligent vehicle highway systems; Learning algorithms; Learning systems; Object recognition; Accurate models; Boosted classifiers; Boosting algorithms; Improved models; Learning techniques; Model accuracies; Model learnings; New

URI

http://hdl.handle.net/1885/37617

Collections

ANU Research Publications

Source

Proceedings of IEEE Intelligent Vehicles Symposium 2008

Type

Conference paper

DOI

10.1109/IVS.2008.4621221

Restricted until

2037-12-31

Downloads

File

Description

01_Overett_On_the_Importance_of_Accurate_2008.pdf (397.09 KB)

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