Double and triple compression-based forgery detection in JPEG images using deep convolutional neural network-Reference-Cited by-同舟云学术

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Double and triple compression-based forgery detection in JPEG images using deep convolutional neural network

Published:2020-03-12 Issue:02 Volume:29 Page:1
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:
Short-container-title:J. Electron. Imag.

Author:

Bakas Jamimamul¹,Ramachandra Sumana¹,Naskar Ruchira²

Affiliation:

1. National Institute of Technology, Department of Computer Science and Engineering, Rourkela, Odisha

2. Indian Institute of Engineering Science and Technology, Department of Information Technology, Shibpu

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. End-to-end image splicing localization based on multi-scale features and residual refinement module;Journal of Electronic Imaging;2023-11-17

2. A Frequency Attention-Based Dual-Stream Network for Image Inpainting Forensics;Mathematics;2023-06-06

3. Three-stage image forgery localization with shallow feature enhancement and attention;Journal of Electronic Imaging;2022-12-21

4. Recognition Model of Counterfeiting Digital Records of Biometric Photographic Image;Tehnički glasnik;2022-02-04

5. An Overview of Double JPEG Compression Detection and Anti-detection;Journal of Information Hiding and Privacy Protection;2022

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