Image Forensics Based on Transfer Learning and Convolutional Neural Network-Reference-Cited by-同舟云学术

Image Forensics Based on Transfer Learning and Convolutional Neural Network

Published:2017-06-20 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 5th ACM Workshop on Information Hiding and Multimedia Security
language:
Short-container-title:

Author:

Zhan Yifeng¹,Chen Yifang¹,Zhang Qiong¹,Kang Xiangui¹

Affiliation:

1. Sun Yat-Sen University, Guangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3082031.3083250

Reference11 articles.

1. Luca Baroffio Luca Bondi Paolo Bestagini and Stefano Tubaro. 2016. Camera identification with deep convolutional networks. arXiv preprint arXiv:1603.01068 (2016). Luca Baroffio Luca Bondi Paolo Bestagini and Stefano Tubaro. 2016. Camera identification with deep convolutional networks. arXiv preprint arXiv:1603.01068 (2016).

2. A Deep Learning Approach to Universal Image Manipulation Detection Using a New Convolutional Layer

3. A machine learning based scheme for double JPEG compression detection

4. Median Filtering Forensics Based on Convolutional Neural Networks

5. Yeong-Taeg Kim. 1997. Contrast enhancement using brightness preserving bihistogram equalization. IEEE transactions on Consumer Electronics 43 1 (1997) 1--8. 10.1109/30.580378 Yeong-Taeg Kim. 1997. Contrast enhancement using brightness preserving bihistogram equalization. IEEE transactions on Consumer Electronics 43 1 (1997) 1--8. 10.1109/30.580378

Cited by 27 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. Detection of tampered real time videos using deep neural networks;Neural Computing and Applications;2024-05-28

2. Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions;Neurocomputing;2024-05

3. Implementation of an Outdoor Camera Sabotage Detection System Model;2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2024-04-27

4. Multimedia Data and Security;IEEE MultiMedia;2024-01

5. Good or Evil: Generative Adversarial Networks in Digital Forensics;Advances in Information Security;2023-11-15