SMDAF: A novel keypoint based method for copy‐move forgery detection-Reference-Cited by-同舟云学术

SMDAF: A novel keypoint based method for copy‐move forgery detection

Author:

Yue Guangyu¹²^ORCID,Duan Qing¹³,Liu Renyang²⁴^ORCID,Peng Wenyu¹²,Liao Yun¹³,Liu Junhui¹³^ORCID

Affiliation:

1. National Pilot School of Software Yunnan University Kuming China

2. Engineering Research Center of Cyberspace Yunnan University Kuming China

3. Key Laboratory in Software Engineering of Yunnan Province Yunnan University Kuming China

4. School of Information Science and Engineering Yunnan University Kuming China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

Reference46 articles.

2. Media forensics on social media platforms: A survey;Pasquini C.;EURASIP J. Inf. Secur.,2021

Cited by 8 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

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