Convolutional Neural Network Architecture for Recovering Watermark Synchronization

In this paper, we propose a convolutional neural network-based template architecture that compensates for the disadvantages of existing watermarking techniques that are vulnerable to geometric distortion. The proposed template consists of a template generation network, a template extraction network,...

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Bibliographic Details
Main Authors: Wook-Hyung Kim, Jihyeon Kang, Seung-Min Mun, Jong-Uk Hou
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/18/5427