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A Pedestrian Detection System With Weak Classifiers

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dc.contributor.authorTetik, Yusuf Engin
dc.contributor.authorBolat, Bulent
dc.date.accessioned2026-06-27T13:19:39Z
dc.date.issued2013
dc.description.abstractIn this paper, a pedestrian detection system which uses sliding window approach to detect pedestrians in still digital images is presented. The proposed pedestrian detection system combines weak classifiers in an Adaboost like novel way to create a strong classifier. Besides, rectangle ratios and discrete cosine transform coefficients are used as features with the well-known rectangle differences method.en
dc.identifier.isbn978-1-4673-5563-6; 978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.14981/51859
dc.identifier.wos000325005300197
dc.language.isotur
dc.publisherIEEE
dc.relation.conference21st Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof2013 21ST SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.subjectpedestrian detection system
dc.subjectsliding window approach
dc.subjectweak classifiers
dc.subjectadaboost
dc.subjectrectangle differences
dc.subjectrectangle ratios
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleA Pedestrian Detection System With Weak Classifiers
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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