Image Forgery and Image Tampering Detection Techniques: A Review-Reference-Cited by-同舟云学术

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Image Forgery and Image Tampering Detection Techniques: A Review

Published:2023 Issue: Volume: Page:159-179
ISSN:2367-3370
Container-title:Proceedings of Third International Conference on Sustainable Expert Systems
language:
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Author:

Nair S. Hridya,Nair Kasthuri A. S.,Padmanabhan Niharika,Remya S.,Ratnakaran Riya

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-7874-6_13

Reference16 articles.

1. Kumar S, Cristin R (2018) A systematic study of image forgery detection. J Comput Theoret Nanosci

2. Myvizhi D, Miraclin Joyce Pamila JC (2022) Extensive analysis of deep learning-based deep fake video detection. J Ubiquit Comput Commun Technol 4(1):1–8

3. Sungheetha A, Rajesh Sharma R (202) Classification of remote sensing image scenes using double feature extraction hybrid deep learning approach. J Inf Technol 3(02):133–149

4. Gardella M, Musé P, Morel J-M, Colom M (2021) Forgery detection in digital images by multi-scale noise estimation. J Imaging

5. Li S-P, Han Z, Chen Y-Z, Fu B, Lu C, Yao X (2010) Resampling forgery detection in JPEG-compressed images. In: 2010 3rd International congress on image and signal processing

Cited by 1 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. FIDD-1500: Fake Image Detection Dataset;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13

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