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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45EK4FB
Repositorysid.inpe.br/sibgrapi/2021/09.16.23.57
Last Update2021:09.16.23.57.12 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.16.23.57.12
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyMedeirosAraúSilvRama:2021:UsImAv
TitleUsing images to avoid collisions and bypass obstacles in indoor environments
FormatOn-line
Year2021
Access Date2024, May 02
Number of Files1
Size220 KiB
2. Context
Author1 Medeiros, David Silva de
2 Araújo, Thiago Henrique
3 Silva Júnior, Elias Teodoro da
4 Ramalho, Geraldo Luis Bezerra
Affiliation1 Federal Institute of Education, Science and Technology of Ceará
2 Federal Institute of Education, Science and Technology of Ceará
3 Federal Institute of Education, Science and Technology of Ceará
4 Federal Institute of Education, Science and Technology of Ceará
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 Addressdavid.silvamm@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2021-09-16 23:57:12 :: david.silvamm@gmail.com -> administrator ::
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsdeep learning
dataset
assistive technology
CNN
AbstractConvolutional Neural Network (CNN) has contributed a lot to the advancement of autonomous navigation techniques, and such systems can be adapted to facilitate the movement of robots and visually impaired people. This work presents an approach that uses images to avoid collisions and bypass obstacles in indoor environments. The constructed dataset uses information from forward and lateral speeds during walks to determine collisions and obstacle avoidance. VGG16, ResNet50, and Dronet architectures were used to evaluate the dataset. Finally, reflections on the dataset characteristics are added, and the CNNs performance is presented.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > Using images to...
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/45EK4FB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45EK4FB
Languageen
Target FileUsing_images_to_avoid_collisions_and_bypass_obstacles_in_indoor_environments.pdf
User Groupdavid.silvamm@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 4
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 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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