Stebėti
Matthew C. Stamm
Matthew C. Stamm
Associate Professor, Drexel University
Patvirtintas el. paštas drexel.edu - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
A deep learning approach to universal image manipulation detection using a new convolutional layer
B Bayar, MC Stamm
Proceedings of the 4th ACM workshop on information hiding and multimedia …, 2016
9152016
Constrained convolutional neural networks: A new approach towards general purpose image manipulation detection
B Bayar, MC Stamm
IEEE Transactions on Information Forensics and Security 13 (11), 2691-2706, 2018
5932018
Information Forensics: An Overview of the First Decade
MC STAMM, MIN WU, K LIU
4572013
Forensic detection of image manipulation using statistical intrinsic fingerprints
MC Stamm, KJR Liu
IEEE Transactions on Information Forensics and Security 5 (3), 492-506, 2010
3882010
Anti-forensics of digital image compression
M Stamm, K Liu
Information Forensics and Security, IEEE Transactions on, 1-1, 2011
2932011
Robust median filtering forensics using an autoregressive model
X Kang, MC Stamm, A Peng, KJR Liu
IEEE Transactions on Information Forensics and Security 8 (9), 1456-1468, 2013
2512013
Temporal forensics and anti-forensics for motion compensated video
MC Stamm, WS Lin, KJR Liu
IEEE Transactions on Information Forensics and Security 7 (4), 1315-1329, 2012
2462012
Anti-forensics of JPEG compression
MC Stamm, SK Tjoa, WS Lin, KJR Liu
2010 IEEE International conference on acoustics, speech and signal …, 2010
1672010
Forensic similarity for digital images
O Mayer, MC Stamm
IEEE Transactions on Information Forensics and Security 15, 1331-1346, 2019
1562019
Blind forensics of contrast enhancement in digital images
M Stamm, KJR Liu
2008 15th IEEE International Conference on Image Processing, 3112-3115, 2008
1492008
Design principles of convolutional neural networks for multimedia forensics
B Bayar, MC Stamm
Electronic Imaging 29, 77-86, 2017
1482017
Undetectable image tampering through JPEG compression anti-forensics
MC Stamm, SK Tjoa, WS Lin, KJR Liu
2010 IEEE international conference on image processing, 2109-2112, 2010
1262010
Forensic estimation and reconstruction of a contrast enhancement mapping
MC Stamm, KJR Liu
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
1142010
Camera model identification framework using an ensemble of demosaicing features
C Chen, MC Stamm
2015 IEEE international workshop on information forensics and security (WIFS …, 2015
1052015
On the robustness of constrained convolutional neural networks to jpeg post-compression for image resampling detection
B Bayar, MC Stamm
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
1012017
Learned forensic source similarity for unknown camera models
O Mayer, MC Stamm
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
932018
Augmented convolutional feature maps for robust cnn-based camera model identification
B Bayar, MC Stamm
2017 IEEE International Conference on Image Processing (ICIP), 4098-4102, 2017
792017
Forensics vs. anti-forensics: A decision and game theoretic framework
MC Stamm, WS Lin, KJR Liu
2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012
782012
Towards open set camera model identification using a deep learning framework
B Bayar, MC Stamm
2018 IEEE international conference on acoustics, speech and signal …, 2018
772018
Accurate and efficient image forgery detection using lateral chromatic aberration
O Mayer, MC Stamm
IEEE Transactions on information forensics and security 13 (7), 1762-1777, 2018
772018
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Straipsniai 1–20