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Comparison of Traditional Haar Classifiers used in Face Detection Applications with an Alternative Classifier for Four Stages Filtering

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dc.creator Armagan, Orhan
dc.creator KAHRİMAN, Mesud
dc.date 2013-12-31T22:00:00Z
dc.date.accessioned 2020-10-06T11:37:37Z
dc.date.available 2020-10-06T11:37:37Z
dc.identifier e3e339c1-8916-4a7b-89ec-dab5c18702ea
dc.identifier 10.1109/siu.2014.6830676
dc.identifier https://avesis.sdu.edu.tr/publication/details/e3e339c1-8916-4a7b-89ec-dab5c18702ea/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/74533
dc.description In this study, haar-like features used for face detection on images and adaboost algorithm have been introduced, and an additional distinctive feature of traditional haar features have been proposed. The performances of recommended feature and traditional haar features in 'CBCL-MIT Center For Biological and Computation Learning' face database on the first 200 containing faces positive images and on the first 400 containing nonfaces negative pictures have been tested and the success rates (%) have been indicated in a table. As a result, the success rate of the supposed feature on face photos in the first three stages have been much higher than traditional haar features.
dc.language tur
dc.rights info:eu-repo/semantics/closedAccess
dc.title Comparison of Traditional Haar Classifiers used in Face Detection Applications with an Alternative Classifier for Four Stages Filtering
dc.type info:eu-repo/semantics/conferenceObject


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