Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3RPAD4E
Repositorysid.inpe.br/sibgrapi/2018/09.03.20.26
Last Update2018:09.03.20.26.47 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2018/09.03.20.26.47
Metadata Last Update2022:06.14.00.09.22 (UTC) administrator
DOI10.1109/SIBGRAPI.2018.00012
Citation KeyLeonardoCarRezZucFar:2018:DeFeCl
TitleDeep Feature-based Classifiers for Fruit Fly Identification (Diptera: Tephritidae)
FormatOn-line
Year2018
Access Date2024, May 05
Number of Files1
Size1375 KiB
2. Context
Author1 Leonardo, Matheus M.
2 Carvalho, Tiago J.
3 Rezende, Edmar
4 Zucchi, Roberto
5 Faria, Fabio A.
Affiliation1 Universidade Federal de São Paulo
2 Federal Institute of São Paulo
3 University of Campinas
4 University of Sao Paulo
5 Universidade Federal de São Paulo
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addressffaria@unifesp.br
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2018-09-03 20:26:47 :: ffaria@unifesp.br -> administrator ::
2022-06-14 00:09:22 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsdeep learning
classification
fruit fly
Anastrepha
AbstractFruit flies has a big biological and economic im- portance for the farming of different tropical and subtropical countries in the World. Specifically in Brazil, third largest fruit producer in the world, the direct and indirect losses caused by fruit flies can exceed USD 120 million/year. These losses are related to production, the cost of pest control and export markets. One of the most economically important fruit flies in the America belong to the genus Anastrepha, which has approximately 300 known species, of which 120 are recorded in Brazil. However, less than 10 species are economically important and are considered pests of quarantine significance by regulatory agencies. The extreme similarity among the species of the genus Anastrepha makes its manual taxonomic classification a nontrivial task, causing onerous and very subjective results. In this work, we propose an approach based on deep learning to assist the scarce specialists, reducing the time of analysis, subjectivity of the classifications and consequently, the economic losses related to these agricultural pests. In our experiments, five deep features and nine machine learning techniques have been studied for the target task. Furthermore, the proposed approach have achieved similar effectiveness results to state-of-art approaches.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2018 > Deep Feature-based Classifiers...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Deep Feature-based Classifiers...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 03/09/2018 17:26 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3RPAD4E
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3RPAD4E
Languageen
Target Filedeep-feature-based.pdf
User Groupffaria@unifesp.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 8
sid.inpe.br/sibgrapi/2022/06.10.21.49 1
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 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


Close