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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Código do Detentoribi 8JMKD3MGPEW34M/46T9EHH
Identificador8JMKD3MGPEW34M/438DG35
Repositóriosid.inpe.br/sibgrapi/2020/09.11.16.08
Última Atualização2020:10.01.14.27.23 (UTC) administrator
Repositório de Metadadossid.inpe.br/sibgrapi/2020/09.11.16.08.08
Última Atualização dos Metadados2022:06.14.00.00.01 (UTC) administrator
DOI10.1109/SIBGRAPI51738.2020.00023
Chave de CitaçãoSantosPireColoPapa:2020:ScChDe
TítuloScene Change Detection Using Multiscale Cascade Residual Convolutional Neural Networks
FormatoOn-line
Ano2020
Data de Acesso17 maio 2024
Número de Arquivos1
Tamanho1872 KiB
2. Contextualização
Autor1 Santos, Daniel Felipe Silva
2 Pires, Rafael Gonçalves
3 Colombo, Danilo
4 Papa, João Paulo
Afiliação1 São Paulo State University (UNESP)
2 São Paulo State University (UNESP)
3 PETROBRAS - BR
4 São Paulo State University (UNESP)
EditorMusse, Soraia Raupp
Cesar Junior, Roberto Marcondes
Pelechano, Nuria
Wang, Zhangyang (Atlas)
Endereço de e-Maildanielfssantos1@gmail.com
Nome do EventoConference on Graphics, Patterns and Images, 33 (SIBGRAPI)
Localização do EventoPorto de Galinhas (virtual)
Data7-10 Nov. 2020
Editora (Publisher)IEEE Computer Society
Cidade da EditoraLos Alamitos
Título do LivroProceedings
Tipo TerciárioFull Paper
Histórico (UTC)2020-10-01 14:27:23 :: danielfssantos1@gmail.com -> administrator :: 2020
2022-06-14 00:00:01 :: administrator -> danielfssantos1@gmail.com :: 2020
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo de Versãofinaldraft
Palavras-Chavechange
detection
learning
multiscale
ResumoScene change detection is an image processing problem related to partitioning pixels of a digital image into foreground and background regions. Mostly, visual knowledge-based computer intelligent systems, like traffic monitoring, video surveillance, and anomaly detection, need to use change detection techniques. Amongst the most prominent detection methods, there are the learning-based ones, which besides sharing similar training and testing protocols, differ from each other in terms of their architecture design strategies. Such architecture design directly impacts on the quality of the detection results, and also in the device resources capacity, like memory. In this work, we propose a novel Multiscale Cascade Residual Convolutional Neural Network that integrates multiscale processing strategy through a Residual Processing Module, with a Segmentation Convolutional Neural Network. Experiments conducted on two different datasets support the effectiveness of the proposed approach, achieving average overall F -measure results of 0.9622 and 0.9664 over Change Detection 2014 and PetrobrasROUTES datasets respectively, besides comprising approximately eight times fewer parameters. Such obtained results place the proposed technique amongst the top four state-of-the-art scene change detection methods.
Arranjo 1urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Scene Change Detection...
Arranjo 2urlib.net > SDLA > Fonds > Full Index > Scene Change Detection...
Conteúdo da Pasta docacessar
Conteúdo da Pasta source
71.pdf 28/09/2020 13:13 1.8 MiB
Conteúdo da Pasta agreement
agreement.html 11/09/2020 13:08 1.2 KiB 
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGPEW34M/438DG35
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGPEW34M/438DG35
Idiomaen
Arquivo Alvo71.pdf
Grupo de Usuáriosdanielfssantos1@gmail.com
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhosid.inpe.br/banon/2001/03.30.15.38.24
Unidades Imediatamente Superiores8JMKD3MGPEW34M/43G4L9S
8JMKD3MGPEW34M/4742MCS
Lista de Itens Citandosid.inpe.br/sibgrapi/2020/10.28.20.46 7
Acervo Hospedeirosid.inpe.br/banon/2001/03.30.15.38
6. Notas
Campos Vaziosarchivingpolicy 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
7. Controle da descrição
e-Mail (login)danielfssantos1@gmail.com
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