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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PJ4R98
Repositorysid.inpe.br/sibgrapi/2017/09.04.16.22
Last Update2017:09.04.16.22.13 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/09.04.16.22.13
Metadata Last Update2022:05.18.22.18.23 (UTC) administrator
Citation KeySymBentRitt:2017:PaImNu
TitleParalelização e implementação na nuvem de algoritmos de detecção de lesões na substância branca do cérebro
FormatOn-line
Year2017
Access Date2024, May 02
Number of Files1
Size300 KiB
2. Context
Author1 Sym, Yan
2 Bento, Mariana
3 Rittner, Leticia
Affiliation1 Faculdade de Engenharia Elétrica e de Computação (FEEC) - Unicamp
2 Faculdade de Engenharia Elétrica e de Computação (FEEC) - Unicamp
3 Faculdade de Engenharia Elétrica e de Computação (FEEC) - Unicamp
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 Addressyan.vsym1@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 TypeUndergraduate Work
History (UTC)2017-09-04 16:22:13 :: yan.vsym1@gmail.com -> 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
Keywordsdetecção de lesões
segmentação de lesões
cérebro humano
WML
MICCAI
ISLES
2015
paralelismo
computação na nuvem
segurança das informações
machine learning
classificação de imagens
análise morfológico
extração de atributos
Support Vector Machine
Random Forest
k-Nearest Neighbors
Amazon EC2
Dice
Acurácia
AbstractExtracting data from images is a time-consuming and computationally demanding process, often requiring specific optimizations and multiple processors. When the dataset is very large and has sensitive content, several challenges arise regarding the storage, transfer, consistency, and privacy of information. This project proposes to study, reproduce and improve methods of identification and segmentation of lesions in the white matter of human brain. Parallel processing and cloud computing algorithms are used aiming at reducing the time needed to process, transfer and store the data without jeopardizing information security.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Paralelização e implementação...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PJ4R98
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PJ4R98
Languagept
Target FileYanSym_SIBGRAPI2017_CameraReady.pdf
User Groupyan.vsym1@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 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


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