Automatic Facial Forgery Detection Using Deep Neural Networks-Reference-Cited by-同舟云学术

Automatic Facial Forgery Detection Using Deep Neural Networks

Published:2021 Issue: Volume: Page:205-214
ISSN:2195-4356
Container-title:Lecture Notes in Mechanical Engineering
language:
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Author:

Chandani Khushi,Arora Monika

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-15-9956-9_21

Reference20 articles.

1. Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv

2. Krizhevsky A, Sutskever I, Hinton G (2012) ImageNet classification with deep convolutional neural networks. In: Neural information processing systems

3. Li J, Shen T, Zhang W, Ren H, Zeng D, Mei T (2019) Zooming into face forensics: a pixel-level analysis

4. Rössler A, Cozzolino D, Verdoliva L, Riess C, Thies J, Nießner M (2019) FaceForensics++: learning to detect manipulated facial images

5. Image recognition & image processing medium. https://medium.com/@Adoriasoft/image-recognition-and-image-processing-techniques-fe3d35d58919. Last accessed 2020/5/3

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