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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PJ8FTL
Repositorysid.inpe.br/sibgrapi/2017/09.05.12.21
Last Update2017:09.05.12.21.34 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.05.12.21.35
Metadata Last Update2022:05.18.22.18.24 (UTC) administrator
Citation KeyLinsRied:2017:MeCoCl
TitleUma metodologia de contagem e classificação de afídeos utilizando visão computacional
FormatOn-line
Year2017
Access Date2025, July 14
Number of Files1
Size2110 KiB
2. Context
Author1 Lins, Elison Alfeu
2 Rieder, Rafael
Affiliation1 Universidade de Passo Fundo
2 Universidade de Passo Fundo
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addresselison.a.lins@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2017-09-05 12:21:35 :: elison.a.lins@gmail.com -> administrator ::
2022-05-18 22:18:24 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsOpenCv
tensorflow
aphids
counting
classification
AbstractAbstractAphids are insects that attack crops and cause damage directly, consuming the sap of plants, and indirectly, transmiting diseases. The counting and classification of these insects are fundamental for measuring and predicting crop hazards and serving as the basis for the application or not of chemicals. Traditionally, the counting process is manual, and depends of microscopes and good eyesight of the specialist, in a time-consuming task susceptible to errors. With this in mind, this paper presents a methodology and a software to automate the counting and classification of aphids using image processing, computer vision and deep learning methods. As preliminary results in a pilot study, we obtained 95.50 % correlation for the count of 28 samples containing Rhopalosiphum padi, in shortest time compared the manual method.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Uma metodologia de...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PJ8FTL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ8FTL
Languagept
Target File2017_sibgrapi_WIP_Elison.pdf
User Groupelison.a.lins@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 51
sid.inpe.br/banon/2001/03.30.15.38.24 6
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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