An Efficient CNN Model to Detect Copy-Move Image Forgery-Reference-Cited by-同舟云学术

An Efficient CNN Model to Detect Copy-Move Image Forgery

Published:2022 Issue: Volume:10 Page:48622-48632
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hosny Khalid M.¹^ORCID,Mortda Akram M.²,Fouda Mostafa M.³^ORCID,Lashin Nabil A.¹

Affiliation:

1. Department of Information Technology, Zagazig University, Zagazig, Egypt

2. Department of Information Technology, Faculty of Information Technology and Computer Science, Sinai University, Arish, Egypt

3. Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09766302.pdf?arnumber=9766302

Reference34 articles.

1. DOA-GAN: Dual-Order Attentive Generative Adversarial Network for Image Copy-Move Forgery Detection and Localization

2. BusterNet: Detecting Copy-Move Image Forgery with Source/Target Localization

3. An End-to-End Dense-InceptionNet for Image Copy-Move Forgery Detection

4. Efficient approach towards detection and identification of copy move and image splicing forgeries using mask R-CNN with MobileNet V1;dhananjay;Comput Intell Neurosci,2022

5. AR-Net: Adaptive Attention and Residual Refinement Network for Copy-Move Forgery Detection

Cited by 24 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. Detecting complex copy-move forgery using KeyPoint-Siamese Capsule Network against adversarial attacks;International Journal of Machine Learning and Cybernetics;2024-09-13

2. A Similarity-Based Positional Attention-Aided Deep Learning Model for Copy–Move Forgery Detection;IEEE Transactions on Artificial Intelligence;2024-09

3. CFDMI-SEC: An optimal model for copy-move forgery detection of medical image using SIFT, EOM and CHM;PLOS ONE;2024-07-23

4. Comparative Analysis of Deep Learning Approaches for Detecting Copy-Move Forgery;2024 International Conference on Computational Intelligence and Computing Applications (ICCICA);2024-05-23

5. Exploring Pseudo-Zernike Moments for Effective Image Forgery Detection;2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN);2024-05-03