Image forgery detection in forensic science using optimization based deep learning models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17316-3.pdf
Reference32 articles.
1. Park JY, Kang TA, Moon YH, Eom IK (2020) Copy-move forgery detection using scale invariant feature and reduced local binary pattern histogram. Symmetry 12(4):492
2. Galvan F (2020) Image/Video forensics: theoretical background, operational approaches and best practices. Eur Police Sci Res Bull 20:105
3. Diallo B, Urruty T, Bourdon P, Fernandez-Maloigne C (2020) Robust forgery detection for compressed images using CNN supervision. Forensic Sci Int Rep 2:100112
4. Xiao B, Wei Y, Bi X, Li W, Ma J (2020) Image splicing forgery detection combining coarse to refined convolutional neural network and adaptive clustering. Inf Sci 511:172–191
5. Dua S, Singh J, Parthasarathy H (2020) Detection and localization of forgery using statistics of DCT and Fourier components. Signal Process Image Commun 82:115778
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