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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3CA2238
Repositorysid.inpe.br/sibgrapi/2012/07.15.23.52
Last Update2012:07.15.23.52.54 ffaria@ic.unicamp.br
Metadatasid.inpe.br/sibgrapi/2012/07.15.23.52.54
Metadata Last Update2020:02.19.02.18.28 administrator
Citation KeyFariaSantRochTorr:2012:AuClFu
TitleAutomatic Classifier Fusion for Produce Recognition
FormatDVD, On-line.
Year2012
Access Date2021, Jan. 24
Number of Files1
Size1106 KiB
Context area
Author1 Faria, Fabio Augusto
2 Santos, Jefersson Alex dos
3 Rocha, Anderson
4 Torres, Ricardo da Silva
Affiliation1 University of Campinas
2 University of Campinas
3 University of Campinas
4 University of Campinas
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
e-Mail Addressffaria@ic.unicamp.br
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto
DateAug. 22-25, 2012
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2012-09-20 16:45:34 :: ffaria@ic.unicamp.br -> administrator :: 2012
2020-02-19 02:18:28 :: administrator -> :: 2012
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsRecognition, Ensemble of Classifiers, Diversity Measures.
AbstractRecognizing different kinds of fruits and vegetables is a common task in supermarkets. This task, however, poses several challenges as it requires the identification of different species of a particular produce and also its variety. Usually, existing computer-based recognition approaches are not automatic and demand long-term and laborious prior training sessions. This paper presents a novel framework for classifier fusion aiming at supporting the automatic recognition of fruits and vegetables in a supermarket environment. The objective is to provide an effective mechanism for combining low-cost classifiers trained for specific classes of interest. The experiments performed demonstrate that the proposed framework yields better results than several related work found in the literature and represents a step forward automatic produce recognition in cashiers of supermarkets.
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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3CA2238
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3CA2238
Languageen
Target File2012-sibgrapi-ffaria-vs-03.pdf
User Groupffaria@ic.unicamp.br
Visibilityshown
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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