Image Forgery Detection by CNN and Pretrained VGG16 Model-Reference-Cited by-同舟云学术

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Image Forgery Detection by CNN and Pretrained VGG16 Model

Published:2022 Issue: Volume: Page:141-152
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Gupta Pranjal Raaj,Sharma Disha,Goel Nidhi

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-6887-6_13

Reference23 articles.

1. Gill NK et al (2017) A review paper on digital image forgery detection techniques. In: 8th international conference on computing, communication and networking technologies (ICCCNT), 1–7

2. Kumar et al (2018) A systematic study of image forgery detection. J Comput Theor Nanosci

3. Potdar VM et al (2005) A survey of digital image watermarking techniques. In: 3rd IEEE international conference on industrial informatics, 709–716

4. Panda S, Mishra M (2005) Passive techniques of digital image forgery detection: developments and challenge. Springer

5. Goodfellow I et al (2016) Deep learning book review health inform resources. The MIT Press

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1. Detecting Post Editing of Multimedia Images using Transfer Learning and Fine Tuning;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-11-16

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