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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JRTTTP
Repositorysid.inpe.br/sibgrapi/2015/07.15.14.59
Last Update2015:07.15.14.59.09 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2015/07.15.14.59.09
Metadata Last Update2022:05.18.22.20.59 (UTC) administrator
Citation KeyMeloAnge:2015:ReAuIn
TitleReconhecimento Automático do Inseto Diaphorina citri em Imagens de Microscopia
FormatOn-line
Year2015
Access Date2024, May 03
Number of Files1
Size352 KiB
2. Context
Author1 Melo, José Leonardo dos Santos
2 Angelo, Michele Fúlvia
Affiliation1 PGCA - Pós-Graduação em Computação Aplicada, UEFS - Universidade Estadual de Feira de Santana
2 PGCA - Pós-Graduação em Computação Aplicada, UEFS - Universidade Estadual de Feira de Santana
EditorRios, Ricardo Araujo
Paiva, Afonso
e-Mail Addressleomelocomputacao@gmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2015-07-15 14:59:09 :: leomelocomputacao@gmail.com -> administrator ::
2022-05-18 22:20:59 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsCitriculture
Yellow Sticky Traps
Diaphorina citri
Huanglongbing (HLB)
Classification of Digital Images
Machine Learning
AbstractThis paper presents a proposal for the use of computational approaches to image classification of insect Diaphorina citri, in microscopy, distinguishing it from other insects commonly found in citrus regions of Sao Paulo, Brazil. In addition, comparisons will be made between the approaches used and optimization of the proposed classifiers. Extractors local features invariant to rotation and scale will be used along with different approaches bag-of-features and will be classified as machine learning algorithms. This work is a significant step to enable the creation of computational systems that automate the important process of counting these insects.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2015 > Reconhecimento Automático do...
doc Directory Contentaccess
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JRTTTP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JRTTTP
Languagept
Target FileID18_Sibgrapi_2015.pdf
User Groupadministrator
leomelocomputacao@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 8
sid.inpe.br/banon/2001/03.30.15.38.24 1
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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