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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3M8SCP5
Repositorysid.inpe.br/sibgrapi/2016/08.11.22.17
Last Update2016:08.11.22.17.00 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/08.11.22.17.01
Metadata Last Update2022:05.18.22.21.07 (UTC) administrator
Citation KeyPereiraBugaSait:2016:ApAtCl
TitleAprendizado ativo para classificação do vigor de sementes de soja
FormatOn-line
Year2016
Access Date2024, May 03
Number of Files1
Size1617 KiB
2. Context
Author1 Pereira, Douglas Felipe
2 Bugatti, Pedro Henrique
3 Saito, Priscila Tiemi Maeda
Affiliation1 Federal University of Technology (UTFPR)
2 Federal University of Technology (UTFPR)
3 Federal University of Technology (UTFPR), University of Campinas (UNICAMP)
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressdouglaspereira@alunos.utfpr.edu.br
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2016-08-11 22:17:01 :: douglaspereira@alunos.utfpr.edu.br -> administrator ::
2022-05-18 22:21:07 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsaprendizado ativo
análise de imagens
processamento de imagens
classificação
sementes de soja
AbstractThe task of providing a high quality grain (e.g. soybean) to the farmer is a key challenge of the agrobusiness field. To achieve such quality considering soybean seeds it is applied the so-called tetrazolium test. This test provides an acurate diagnosis of the damages found in the seed, such as lacerations caused by insects, mechanical damages or high rates of humidity. These damages cause a considerable quality reduction and directly impact in the seed vigor. Some traditional machine learning methods were applied to the context of seed crops, in order to automatic classify the seed vigor. However, the great majority of the researches use the traditional supervised learning paradigm. Thus, in this paper we proposed to exploit the active learning paradigm to perform the classification of the seed vigor, derived from the tetrazolium test.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > Aprendizado ativo para...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3M8SCP5
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3M8SCP5
Languagept
Target File2016-sibgrapi-wip.pdf
User Groupdouglaspereira@alunos.utfpr.edu.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 7
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi 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 versiontype volume


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