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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/47MNHJP
Repositorysid.inpe.br/sibgrapi/2022/09.27.23.59
Last Update2022:09.27.23.59.44 (UTC) raimundo.vasconcelos@ifb.edu.br
Metadata Repositorysid.inpe.br/sibgrapi/2022/09.27.23.59.44
Metadata Last Update2023:05.23.04.20.43 (UTC) administrator
Citation KeyLacerdaVasc:2022:MaLeAp
TitleA Machine Learning Approach for DeepFake Detection
FormatOn-line
Year2022
Access Date2024, July 27
Number of Files1
Size648 KiB
2. Context
Author1 Lacerda, Gustavo Cunha
2 Vasconcelos, Raimundo Claudio da Silva
Affiliation1 Instituto Federal de Brasília
2 Instituto Federal de Brasília
e-Mail Addressustavocunhalacerda@gmail.com
Conference NameConference on Graphics, Patterns and Images, 35 (SIBGRAPI)
Conference LocationNatal, RN
Date24-27 Oct. 2022
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2022-09-27 23:59:44 :: raimundo.vasconcelos@ifb.edu.br -> administrator ::
2023-05-23 04:20:43 :: administrator -> :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsDeepfake
Machine Learning
Image |Processing
AbstractWith the spread of DeepFake techniques, this technology has become quite accessible and good enough that there is concern about its malicious use. Faced with this problem, detecting forged faces is of utmost importance to ensure security and avoid socio-political problems, both on a global and private scale. This paper presents a solution for the detection of DeepFakes using convolution neural networks and a dataset developed for this purpose - Celeb-DF. The results show that, with an overall accuracy of 95% in the classification of these images, the proposed model is close to what exists in the state of the art with the possibility of adjustment for better results in the manipulation techniques that arise in the future.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2022 > A Machine Learning...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/47MNHJP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/47MNHJP
Languageen
Target Filepibic_gustavo_2022_toSIBIGRAPI-2.pdf
User Groupraimundo.vasconcelos@ifb.edu.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/495MHJ8
Citing Item Listsid.inpe.br/sibgrapi/2023/05.19.12.10 13
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 editor electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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