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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/UNhVf
Repositorysid.inpe.br/sibgrapi@80/2008/07.18.15.15
Last Update2008:07.18.15.15.40 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2008/07.18.15.15.42
Metadata Last Update2022:06.14.00.13.46 (UTC) administrator
DOI10.1109/SIBGRAPI.2008.9
Citation KeyRochaHauaWainGold:2008:AuPrCl
TitleAutomatic produce classification from images using color, texture and appearance cues
FormatPrinted, On-line.
Year2008
Access Date2024, May 02
Number of Files1
Size418 KiB
2. Context
Author1 Rocha, Anderson
2 Hauagge, Daniel C.
3 Wainer, Jacques
4 Goldenstein, Siome
Affiliation1 Institute of Computing, University of Campinas (Unicamp)
2 Institute of Computing, University of Campinas (Unicamp)
3 Institute of Computing, University of Campinas (Unicamp)
4 Institute of Computing, University of Campinas (Unicamp)
EditorJung, Cláudio Rosito
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 21 (SIBGRAPI)
Conference LocationCampo Grande, MS, Brazil
Date12-15 Oct. 2008
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2008-07-18 15:15:42 :: anderson.rocha@ic.unicamp.br -> administrator ::
2009-08-13 20:38:56 :: administrator -> anderson.rocha@ic.unicamp.br ::
2010-08-28 20:03:22 :: anderson.rocha@ic.unicamp.br -> administrator ::
2022-06-14 00:13:46 :: administrator -> :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsProduce classification
multi-class categorization
produce data set
AbstractWe propose a system to solve a multi-class produce categorization problem. For that, we use statistical color, texture, and structural appearance descriptors (bag-of-features). As the best combination setup is not known for our problem, we combine several individual features from the state-of-the-art in many different ways to assess how they interact to improve the overall accuracy of the system. We validate the system using an image data set collected on our local fruits and vegetables distribution center.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2008 > Automatic produce classification...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Automatic produce classification...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/UNhVf
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/UNhVf
Languageen
Target Filerocha-AutomaticProduceClassification.pdf
User Groupanderson.rocha@ic.unicamp.br
administrator
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SG4TH
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.04.55 2
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress 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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