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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
Date Issue: 2017
Appears in Collections:IC - Artigos e Outros Documentos

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