Data-driven feature characterization techniques for laser printer attribution

Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/353428

Type:	Artigo
Title:	Data-driven feature characterization techniques for laser printer attribution
Author:	Ferreira, Anselmo Bondi, Luca Baroffio, Luca Bestagini, Paolo Huang, Jiwu dos Santos, Jefersson A. Tubaro, Stefano Rocha, Anderson
Abstract:	Laser printer attribution is an increasing problem with several applications, such as pointing out the ownership of crime proofs and authentication of printed documents. However, as commonly proposed methods for this task are based on custom-tailored feat
Subject:	Impressoras laser Aprendizado profundo Redes neurais convolucionais Laser printers Deep learning Convolutional neural networks
Country:	Estados Unidos
Editor:	Institute of Electrical and Electronics Engineers
Rights:	Fechado
Identifier DOI:	10.1109/TIFS.2017.2692722
Address:	https://ieeexplore.ieee.org/document/7895220
Date Issue:	2017
Appears in Collections:	IC - Artigos e Outros Documentos

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