Image Forgery Detection and Localization via a Reliability Fusion Map

Moving away from hand-crafted feature extraction, the use of data-driven convolution neural network (CNN)-based algorithms facilitates the realization of end-to-end automated forgery detection in multimedia forensics. On the basis of fingerprints acquired by images from different camera models, the...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 20; H. 22; S. 6668
Hauptverfasser:	Yao, Hongwei, Xu, Ming, Qiao, Tong, Wu, Yiming, Zheng, Ning
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 21.11.2020 MDPI
Schlagworte:	Accuracy Algorithms convolution neural network (CNN) Design Digital cameras digital image forensics Forgery Internet of Things Multimedia Neural networks Noise reliability fusion map (RFM) Sensors tampering detection and localization
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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