Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PJ4KFL
Repositorysid.inpe.br/sibgrapi/2017/09.04.15.12
Last Update2017:09.04.15.12.42 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.04.15.12.42
Metadata Last Update2022:05.18.22.18.23 (UTC) administrator
Citation KeyLeonardoFari:2017:MiImRe
TitleMid-level Image Representation for Fruit Crop Pest Identification
FormatOn-line
Year2017
Access Date2025, July 09
Number of Files1
Size460 KiB
2. Context
Author1 Leonardo, Matheus Macedo
2 Faria, Fabio Augusto
Affiliation1 Federal University of Sao Paulo
2 Federal University of Sao Paulo
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 Addressffaria@unifesp.br
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 TypeUndergraduate Work
History (UTC)2017-09-04 15:12:42 :: ffaria@unifesp.br -> administrator ::
2022-05-18 22:18:23 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsfruit fly
local descriptor
insect recognition
image classification
AbstractFruit flies are of huge biological and economic importance for the farming of different countries in the World, especially for Brazil. Brazil is the third largest fruit producer in the world with 44 million tons in 2016. The direct and indirect losses caused by fruit flies can exceed USD 2 billion, putting these pests as one of the biggest problems of the world agriculture. In Brazil, it is estimated that the economic losses directly related to production, the cost of pest control and in the loss of export markets, are between USD 120 and 200 million/year. We propose to apply mid-level image representations based on local descriptors for fruit fly identification tasks of three species of the genus Anastrepha. In our experiments, several local image descriptors based on keypoints and machine learning techniques have been compared in the target task. Furthermore, the proposed approaches have achieved excellent effectiveness results when compared with a state-of-art technique.
Arrangementurlib.net > Fonds > SIBGRAPI 2017 > Mid-level Image Representation...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 04/09/2017 12:12 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PJ4KFL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ4KFL
Languageen
Target Filewuw-moscas.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/3PKCC58
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 52
sid.inpe.br/banon/2001/03.30.15.38.24 5
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


Close