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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45EK7EB
Repositorysid.inpe.br/sibgrapi/2021/09.17.00.33
Last Update2021:09.17.00.33.45 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.17.00.33.45
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyGalvãoReSaOlDuAn:2021:AvMoDe
TitleAvaliação de Modelos de Detecção de Objetos para Detectar Glomérulos em Imagens Histológicas
FormatOn-line
Year2021
Access Date2024, May 04
Number of Files1
Size22428 KiB
2. Context
Author1 Galvão, Abel Ramalho
2 Rehem, Jonathan Moreira Cardozo
3 Santos, Washington Luís Conrado dos
4 Oliveira, Luciano Rebouças de
5 Duarte, Angelo Amâncio
6 Angelo, Michele Fúlvia
Affiliation1 Universidade Estadual de Feira de Santana (UEFS)
2 Universidade Estadual de Feira de Santana (UEFS)
3 Centro de Pesquisas Gonçalo Muniz da Fundação Oswaldo Cruz (CpqGM/FIOCRUZ)
4 Universidade Federal da Bahia (UFBA)
5 Universidade Estadual de Feira de Santana (UEFS)
6 Universidade Estadual de Feira de Santana (UEFS)
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressabel.ramalho18@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2021-09-17 00:33:45 :: abel.ramalho18@gmail.com -> administrator ::
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsGlomérulos
Detecção automática
Deep learning
PathoSpotter
AbstractGlomeruli are renal structures responsible for filtering blood and can be affected by lesions. Currently, computer systems to help identify these lesions have been developed, and thus, the detection of these glomeruli is of great importance. The objective of this work is to evaluate the performance of object detection models for the detection of glomeruli in digital histological images. Three models were evaluated: SM1 (SSD Mobilenet v1), FRR50 (Faster RCNN Resnet 50) and FRR101 (Faster RCNN Resnet 101), of which the FRR50 model obtained the best result, mAP=0.88.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > Avaliação de Modelos...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 16/09/2021 21:33 1.3 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45EK7EB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45EK7EB
Languagept
Target Filepaper.pdf
User Groupabel.ramalho18@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 6
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage 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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