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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3CF53LS
Repositorysid.inpe.br/sibgrapi/2012/08.16.10.43
Last Update2012:08.16.10.43.36 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2012/08.16.10.43.36
Metadata Last Update2022:06.14.00.07.40 (UTC) administrator
DOI10.1109/SIBGRAPI.2012.41
Citation KeyEl-DinMousMahd:2012:MiTwGe
TitleA mixture of two gender classification experts
FormatDVD, On-line.
Year2012
Access Date2024, May 05
Number of Files1
Size304 KiB
2. Context
Author1 El-Din, Yomna Safaa
2 Moustafa, Mohamed N.
3 Mahdi, Hani
Affiliation1 Department of Computer and Systems Engineering, Ain Shams University, Cairo, Egypt 
2 Department of Computer Science and Engineering, American University in Cairo, New Cairo, Egypt 
3 Department of Computer and Systems Engineering, Ain Shams University, Cairo, Egypt
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressyomna.safaa-eldin@eng.asu.edu.eg
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto, MG, Brazil
Date22-25 Aug. 2012
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2012-09-20 16:45:35 :: yomna.safaa-eldin@eng.asu.edu.eg -> administrator :: 2012
2022-03-08 21:03:25 :: administrator -> menottid@gmail.com :: 2012
2022-03-10 12:53:08 :: menottid@gmail.com -> administrator :: 2012
2022-06-14 00:07:40 :: administrator -> :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordscommittee machines
Bayes
gender classification
AbstractThis paper presents a novel method for combining the outputs of different gender classification techniques based on facial images. Merging the methods is performed by a committee machine using the Bayesian theorem. We implement and compare several well-known individual classifiers on four different datasets, then we experiment the proposed machine, and show that it significantly improves the accuracy of classification compared to individual classifiers. We also include results that address the effect of scale on the performance of classifiers.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2012 > A mixture of...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > A mixture of...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 16/08/2012 07:43 0.7 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3CF53LS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3CF53LS
Languageen
Target File101351_CameraReadyIEEE.pdf
User Groupyomna.safaa-eldin@eng.asu.edu.eg
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SL8GS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.03.31 8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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