1. Identificação | |
Tipo de Referência | Artigo em Evento (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Código do Detentor | ibi 8JMKD3MGPEW34M/46T9EHH |
Identificador | 8JMKD3MGPEW34M/438DG35 |
Repositório | sid.inpe.br/sibgrapi/2020/09.11.16.08 |
Última Atualização | 2020:10.01.14.27.23 (UTC) administrator |
Repositório de Metadados | sid.inpe.br/sibgrapi/2020/09.11.16.08.08 |
Última Atualização dos Metadados | 2022:06.14.00.00.01 (UTC) administrator |
DOI | 10.1109/SIBGRAPI51738.2020.00023 |
Chave de Citação | SantosPireColoPapa:2020:ScChDe |
Título | Scene Change Detection Using Multiscale Cascade Residual Convolutional Neural Networks |
Formato | On-line |
Ano | 2020 |
Data de Acesso | 17 maio 2024 |
Número de Arquivos | 1 |
Tamanho | 1872 KiB |
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2. Contextualização | |
Autor | 1 Santos, Daniel Felipe Silva 2 Pires, Rafael Gonçalves 3 Colombo, Danilo 4 Papa, João Paulo |
Afiliação | 1 São Paulo State University (UNESP) 2 São Paulo State University (UNESP) 3 PETROBRAS - BR 4 São Paulo State University (UNESP) |
Editor | Musse, Soraia Raupp Cesar Junior, Roberto Marcondes Pelechano, Nuria Wang, Zhangyang (Atlas) |
Endereço de e-Mail | danielfssantos1@gmail.com |
Nome do Evento | Conference on Graphics, Patterns and Images, 33 (SIBGRAPI) |
Localização do Evento | Porto de Galinhas (virtual) |
Data | 7-10 Nov. 2020 |
Editora (Publisher) | IEEE Computer Society |
Cidade da Editora | Los Alamitos |
Título do Livro | Proceedings |
Tipo Terciário | Full 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 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Tipo de Versão | finaldraft |
Palavras-Chave | change detection learning multiscale |
Resumo | Scene 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 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Scene Change Detection... |
Arranjo 2 | urlib.net > SDLA > Fonds > Full Index > Scene Change Detection... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | 71.pdf | 28/09/2020 13:13 | 1.8 MiB | |
Conteúdo da Pasta agreement | |
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4. Condições de acesso e uso | |
URL dos dados | http://urlib.net/ibi/8JMKD3MGPEW34M/438DG35 |
URL dos dados zipados | http://urlib.net/zip/8JMKD3MGPEW34M/438DG35 |
Idioma | en |
Arquivo Alvo | 71.pdf |
Grupo de Usuários | danielfssantos1@gmail.com |
Visibilidade | shown |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Repositório Espelho | sid.inpe.br/banon/2001/03.30.15.38.24 |
Unidades Imediatamente Superiores | 8JMKD3MGPEW34M/43G4L9S 8JMKD3MGPEW34M/4742MCS |
Lista de Itens Citando | sid.inpe.br/sibgrapi/2020/10.28.20.46 7 |
Acervo Hospedeiro | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notas | |
Campos Vazios | 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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7. Controle da descrição | |
e-Mail (login) | danielfssantos1@gmail.com |
atualizar | |
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