Identity statement area | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 8JMKD3MGPAW/3PJ4KFL |
Repository | sid.inpe.br/sibgrapi/2017/09.04.15.12 |
Last Update | 2017:09.04.15.12.42 ffaria@unifesp.br |
Metadata | sid.inpe.br/sibgrapi/2017/09.04.15.12.42 |
Metadata Last Update | 2020:02.20.22.06.46 administrator |
Citation Key | LeonardoFari:2017:MiImRe |
Title | Mid-level Image Representation for Fruit Crop Pest Identification  |
Format | On-line |
Year | 2017 |
Access Date | 2021, Jan. 26 |
Number of Files | 1 |
Size | 460 KiB |
Context area | |
Author | 1 Leonardo, Matheus Macedo 2 Faria, Fabio Augusto |
Affiliation | 1 Federal University of Sao Paulo 2 Federal University of Sao Paulo |
Editor | Torchelsen, 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 Address | ffaria@unifesp.br |
Conference Name | Conference on Graphics, Patterns and Images, 30 (SIBGRAPI) |
Conference Location | Niterói, RJ |
Date | Oct. 17-20, 2017 |
Book Title | Proceedings |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Tertiary Type | Undergraduate Work |
History | 2017-09-04 15:12:42 :: ffaria@unifesp.br -> administrator :: 2020-02-20 22:06:46 :: administrator -> :: 2017 |
Content and structure area | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | fruit fly, local descriptor, insect recognition, image classification. |
Abstract | Fruit 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. |
source Directory Content | there are no files |
agreement Directory Content | |
Conditions of access and use area | |
data URL | http://urlib.net/rep/8JMKD3MGPAW/3PJ4KFL |
zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3PJ4KFL |
Language | en |
Target File | wuw-moscas.pdf |
User Group | ffaria@unifesp.br |
Visibility | shown |
Update Permission | not transferred |
Allied materials area | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPAW/3PJT9LS 8JMKD3MGPAW/3PKCC58 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
Notes area | |
Empty Fields | accessionnumber archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
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