A Review on Automatic Image Forgery Classification Using Advanced Deep Learning Techniques
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-5292-0_1
Reference18 articles.
1. Barad ZJ, Goswami MM (2020) Image forgery detection using deep learning: a survey. In: 2020 6th international conference on advanced computing and communication systems (ICACCS), April
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3. Zhang Y, Goh J, Win LL, Thing VL (2016) Image region forgery detection: a deep learning approach. In: SG-CRC, pp 1–11
4. Bondi L, Lameri S, Güera D, Bestagini P, Delp EJ, Tubaro S (2017) Tampering detection and localization through clustering of camera-based CNN features. In: IEEE conference on computer vision and pattern recognition workshops (CVPRW), pp 1855–1864
5. Bayar B, Stamm MC (2016) A deep learning approach to universal image manipulation detection using a new convolutional layer. In: Proceedings of the 4th ACM workshop on information hiding and multimedia security, pp 5–10
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