Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Shenghai Luo"'
Publikováno v:
IEEE Access, Vol 7, Pp 28525-28538 (2019)
Median filtering, due to highly non-linear and content-preserving, has widely used in the multimedia security fields, such as anti-forensics, steganography, and steganalysis. In the past decade, many excellent algorithms have been proposed, and have
Externí odkaz:
https://doaj.org/article/a09bd19b86984594be99dd6177c15e5a
Publikováno v:
IEEE Access, Vol 7, Pp 80614-80621 (2019)
This paper addresses the median filtering forensics for a lossy compressed image with low resolution, which is essential for the identification of fake images and fake videos. A deep residual model with training data augmentation is employed in the p
Externí odkaz:
https://doaj.org/article/5ffc26cd2c204b33bb562317e4203254
Publikováno v:
Computers, Materials & Continua. 65:2217-2231
Autor:
Wanyi Zhuang, Changtao Miao, Shan He, Hefei Ling, Yutong Yao, Wei Wang, Zhiliang Xu, Xiaoyan Wu, Baoying Chen, Guosheng Zhang, Yuezun Li, Han Chen, Shenghai Luo, Hongxing Fan, Qi Li, Boyuan Liu, Yanjie Hu, Zhenan Sun, Junrui Huang, Jing Dong, Changlei Lu, Bo Peng, Siwei Lyu
Publikováno v:
IJCB
This paper presents a summary of the DeepFake Game Competition (DFGC) 20211. DeepFake technology is developing fast, and realistic face-swaps are increasingly deceiving and hard to detect. At the same time, DeepFake detection methods are also improvi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d41c39fc8a899cc1952a44841701795
http://arxiv.org/abs/2106.01217
http://arxiv.org/abs/2106.01217
Publikováno v:
IEEE Access, Vol 7, Pp 28525-28538 (2019)
Median filtering, due to highly non-linear and content-preserving, has widely used in the multimedia security fields, such as anti-forensics, steganography, and steganalysis. In the past decade, many excellent algorithms have been proposed, and have
Publikováno v:
Neural Information Processing ISBN: 9783030638320
ICONIP (2)
ICONIP (2)
Adversarial images which can fool deep neural networks attract researchers’ attentions to the security of machine learning. In this paper, we employ a blind forensic method to detect adversarial images which are generated by the gradient-based atta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8c24f3408dc1ef44bebc4942a405076
https://doi.org/10.1007/978-3-030-63833-7_35
https://doi.org/10.1007/978-3-030-63833-7_35
Publikováno v:
ACM TUR-C
Sensor noise caused by photo response non-uniformity (PRNU) has been widely accepted as a reliable fingerprint for source camera identification (SCI). In the sensor based camera identification methods, the extracted noise from a test image needs to b