UM
ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm—ISABoost based application in scene categorization
Xueming Qian1,2; Yuan Yan Tang2; Zhe Yan1; Kaiyu Hang1
2013-03-01
Source PublicationNeurocomputing
ISSN0925-2312
Volume103Pages:104-113
Abstract

AdaBoost algorithms fuse weak classifiers to be a strong classifier by adaptively determine fusion weights of weak classifiers. In this paper, an enhanced AdaBoost algorithm by adjusting inner structure of weak classifiers (ISABoost) is proposed. In the traditional AdaBoost algorithms, the weak classifiers are not changed once they are trained. In ISABoost, the inner structures of weak classifiers are adjusted before their fusion weights determination. ISABoost inherits the advantages of the AdaBoost algorithms in fusing weak classifiers to be a strong classifier. ISABoost gives each weak classifier a second chance to be adjusted stronger. The adjusted weak classifiers are more contributive to make correct classifications for the hardest samples. To show the effectiveness of the proposed ISABoost algorithm, its applications in scene categorization are evaluated. Comparisons of ISABoost and AdaBoost algorithms on three widely utilized scene datasets show the effectiveness of ISABoost algorithm.

KeywordAdaboost Scene Categorization Pattern Classification Back-propagation Networks Svm Weight Learning
DOIhttps://doi.org/10.1016/j.neucom.2012.09.011
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science
WOS IDWOS:000313374500011
PublisherELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
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Citation statistics
Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorXueming Qian
Affiliation1.School of Electronic and Information Engineering, Xi’an Jiaotong University, Xianning Road, Xi’an, China
2.Faculty of Science and Technology, The University of Macau, Macau, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Xueming Qian,Yuan Yan Tang,Zhe Yan,et al. ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm—ISABoost based application in scene categorization[J]. Neurocomputing,2013,103:104-113.
APA Xueming Qian,Yuan Yan Tang,Zhe Yan,&Kaiyu Hang.(2013).ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm—ISABoost based application in scene categorization.Neurocomputing,103,104-113.
MLA Xueming Qian,et al."ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm—ISABoost based application in scene categorization".Neurocomputing 103(2013):104-113.
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