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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45BU8FB
Repositorysid.inpe.br/sibgrapi/2021/08.31.15.06
Last Update2021:08.31.15.29.21 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/08.31.15.06.11
Metadata Last Update2022:06.14.00.00.18 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00022
Citation KeySilvaMiraCord:2021:NeGrCr
TitleA New Grammar for Creating Convolutional Neural Networks Applied to Medical Image Classification
FormatOn-line
Year2021
Access Date2024, May 06
Number of Files1
Size350 KiB
2. Context
Author1 da Silva, Cleber Alberto Cabral Ferreira
2 Miranda, Péricles Barbosa Cunha
3 Cordeiro, Filipe Rolim
Affiliation1 Federal Rural University of Pernambuco (UFRPE) 
2 Federal Rural University of Pernambuco (UFRPE) 
3 Federal Rural University of Pernambuco (UFRPE)
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 Addresscleber.cabral@ufrpe.br
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-08-31 15:29:22 :: cleber.cabral@ufrpe.br -> administrator :: 2021
2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:38:15 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:18 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsgrammatical evolution
deep neural networks
multi-objective optimization
AbstractIn the last decade, the adoption of Deep Convolutional Neural Networks (CNNs) has been successfully applied to solve computer vision tasks, such as image classification in the medical field. However, the several architectures proposed in the literature are composed of an increasing number of parameters and complexity. Therefore, finding the optimal trade-off between accuracy and model complexity for a given data set is challenging. To help the search for these suitable configurations, this work proposes using a new Context-Free Grammar associated with a Multi-Objective Grammatical Evolution Algorithm that generates suitable CNNs for a given image classification problem. In this structure, the new grammar maps every possible search space for the creation of networks. Furthermore, the Multi-Objective Grammatical Evolution Algorithm used optimizes this search taking into account two objective functions: accuracy and f1-score. Our proposal was used in three medical image datasets from MedMNIST: PathMNIST, OCTMNIST, and OrganMNIST_Axial. The results showed that our method generated simpler networks with equal or superior performance from state-of-the-art (more complex) networks and others CNNs also generated by grammatical evolution process.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > A New Grammar...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > A New Grammar...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 31/08/2021 12:06 1.3 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45BU8FB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45BU8FB
Languageen
Target File2021171880.pdf
User Groupcleber.cabral@ufrpe.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 5
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


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