An End-to-End Approach for Seam Carving Detection Using Deep Neural Networks

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Wolverhampton-
Autor(es): dc.creatorMoreira, Thierry P.-
Autor(es): dc.creatorSantana, Marcos Cleison S.-
Autor(es): dc.creatorPassos, Leandro A.-
Autor(es): dc.creatorPapa, João Paulo-
Autor(es): dc.creatorda Costa, Kelton Augusto P.-
Data de aceite: dc.date.accessioned2025-08-21T18:46:38Z-
Data de disponibilização: dc.date.available2025-08-21T18:46:38Z-
Data de envio: dc.date.issued2023-03-02-
Data de envio: dc.date.issued2023-03-02-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-031-04881-4_35-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/241821-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/241821-
Descrição: dc.descriptionSeam carving is a computational method capable of resizing images for both reduction and expansion based on its content, instead of the image geometry. Although the technique is mostly employed to deal with redundant information, i.e., regions composed of pixels with similar intensity, it can also be used for tampering images by inserting or removing relevant objects. Therefore, detecting such a process is of extreme importance regarding the image security domain. However, recognizing seam-carved images does not represent a straightforward task even for human eyes, and robust computation tools capable of identifying such alterations are very desirable. In this paper, we propose an end-to-end approach to cope with the problem of automatic seam carving detection that can obtain state-of-the-art results. Experiments conducted over public and private datasets with several tampering configurations evidence the suitability of the proposed model.-
Descrição: dc.descriptionPetrobras-
Descrição: dc.descriptionDepartment of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01-
Descrição: dc.descriptionCMI Lab School of Engineering and Informatics University of Wolverhampton-
Descrição: dc.descriptionDepartment of Computing São Paulo State University, Av. Eng. Luiz Edmundo Carrijo Coube, 14-01-
Formato: dc.format447-457-
Idioma: dc.languageen-
Relação: dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectConvolutional neural networks-
Palavras-chave: dc.subjectImage security-
Palavras-chave: dc.subjectSeam carving-
Título: dc.titleAn End-to-End Approach for Seam Carving Detection Using Deep Neural Networks-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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