1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45F7NEB |
Repository | sid.inpe.br/sibgrapi/2021/09.20.13.36 |
Last Update | 2021:09.20.13.36.18 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.20.13.36.18 |
Metadata Last Update | 2022:09.10.00.16.17 (UTC) administrator |
Citation Key | SilvaAngeSantLoul:2021:MoCo |
Title | Aprendizado Profundo na Classificação de Lesões Crescentes Glomerulares: modelos e condições |
Format | On-line |
Year | 2021 |
Access Date | 2024, May 03 |
Number of Files | 1 |
Size | 1505 KiB |
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2. Context | |
Author | 1 Silva, Joacy Mesquita da 2 Angelo, Michele Fúlvia 3 Santos, Washington L. C. dos 4 Loula, Angelo C |
Affiliation | 1 Universidade Estadual de Feira de Santana (UEFS) 2 Universidade Estadual de Feira de Santana (UEFS) 3 Fundação Oswaldo Cruz - Instituto Gonçalo Moniz 4 Universidade Estadual de Feira de Santana (UEFS) |
Editor | Paiva, 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 Address | angelocl@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Book Title | Proceedings |
Tertiary Type | Work in Progress |
History (UTC) | 2021-09-20 13:36:18 :: angelocl@gmail.com -> administrator :: 2022-09-10 00:16:17 :: administrator -> :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | deep learning glomerular crescent nephropathology |
Abstract | Glomeruli are structures in the kidneys, responsible for filtering the blood, that can be affected by several lesions, such as the glomerular crescent, which is characterized by abnormal cell proliferation. In this work, different models and conditions for the application of deep learning are to evaluated in the task of classifying glomerular crescent histopathological images. The pre-trained networks Xception, InceptionV3, MobileNet, VGG16 and ResNet50 were compared, by applying to the classification of images with crescent vs normal glomeruli. Comparing the accuracy, precision, recall and f1-score of the models, the ResNet50 showed significantly better performance than the other networks, in all measures. The application of data augmentation did not result in a significant improvement in the results in this case. In an experiment of classification of crescent vs non-crescent glomeruli, adding images of three other lesions to the database, the application of Focal Loss presented greater accuracy and precision. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Aprendizado Profundo na... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45F7NEB |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45F7NEB |
Language | pt |
Target File | Artigo_WIP_SIBGRAPI_Aprendizado_Profundo_na_Classifica__o_de_Les_es_Crescentes_Glomerulares__modelos_e_condi__es.pdf |
User Group | angelocl@gmail.com |
Visibility | shown |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 5 sid.inpe.br/banon/2001/03.30.15.38.24 3 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy 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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