1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45CKLG2 |
Repository | sid.inpe.br/sibgrapi/2021/09.04.19.57 |
Last Update | 2021:09.04.19.57.36 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.04.19.57.36 |
Metadata Last Update | 2022:06.14.00.00.25 (UTC) administrator |
DOI | 10.1109/SIBGRAPI54419.2021.00056 |
Citation Key | DouradoNetoGuthCampWeig:2021:DoAdHo |
Title | Domain Adaptation for Holistic Skin Detection  |
Format | On-line |
Year | 2021 |
Access Date | 2025, Mar. 21 |
Number of Files | 1 |
Size | 1718 KiB |
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2. Context | |
Author | 1 Dourado Neto, Aloisio 2 Guth, Frederico 3 Campos, Teofilo de 4 Weigang, Li |
Affiliation | 1 Universidade de Brasília 2 Universidade de Brasília 3 Universidade de Brasília 4 Universidade de Brasília |
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 | aloisio.dourado.bh@gmail.com.br |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2021-09-04 19:57:36 :: aloisio.dourado.bh@gmail.com.br -> administrator :: 2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021 2022-03-02 13:24:27 :: menottid@gmail.com -> administrator :: 2021 2022-06-14 00:00:25 :: administrator -> :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | computer vision deep learning semantic segmentation skin detection domain adaptation |
Abstract | Human skin detection in images is a widely studied topic of Computer Vision for which it is commonly accepted that analysis of pixel color or local patches may suffice. However, we found that the lack of contextual information may hinder the performance of local approaches. In this paper, we present a comprehensive evaluation of holistic and local Convolutional Neural Network (CNN) approaches on in-domain and cross-domain experiments and compare them with state-of-the-art pixel-based approaches. We also propose combining inductive transfer learning and unsupervised domain adaptation methods evaluated on different domains under several amounts of labelled data availability. We show a clear superiority of CNN over pixel-based approaches even without labeled training samples on the target domain and provide experimental support for the superiority of holistic over local approaches for human skin detection. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Domain Adaptation for... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Domain Adaptation for... |
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/45CKLG2 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45CKLG2 |
Language | en |
Target File | SIBGRAP_paper_39__Domain_Adaptation_for_Holistic_Skin_Detection.pdf |
User Group | aloisio.dourado.bh@gmail.com.br |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 97 sid.inpe.br/sibgrapi/2022/06.10.21.49 5 |
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 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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