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Own and others' confidence in social information use. [PDF]

iScience
Gradassi A, van den Bos W, Molleman L.
europepmc   +1 more source

Multi-resolution transfer learning for tampered image classification using SE-enhanced fused-MBConv and optimized CNN heads. [PDF]

Sci Rep
Korsipati JR, Yanamala RMR, Pallakonda A, Raj RDA, Prakasha KK.   +4 more
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Multi-omics analysis identifies CKLF as a promoter for HCC progression by regulating the AKT, ERK pathways, and infiltrating immune cells. [PDF]

Transl Oncol
Peng L, Li J, Yuan J, Ma S, Jin L, Zou G, Tang L.   +6 more
europepmc   +1 more source

Unravelling the genetic architecture of cardiovascular disease through structural variant detection with whole-genome sequencing. [PDF]

Front Genet
Colombage DNP, Moses EK, Melton PE.
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Copy-Paste Augmentation Improves Automatic Species Identification in Camera Trap Images. [PDF]

Ecol Evol
Mesnage CS, Corbett A, Curry J, Rowlands S, Dutta A, Everson R, Simmons BI.   +6 more
europepmc   +1 more source

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Copy-move forgery detection based on hybrid features

Engineering Applications of Artificial Intelligence, 2017
Abstract Copy-move forgery is one of the most popular tampering artifacts in digital images. Most existing keypoint-based detection methods may fail to precisely locate duplicated regions because there are not enough correct matched points. In this paper, a novel copy-move forgery detection method is proposed based on hybrid features.
Wei Lu, Jian Weng
exaly   +2 more sources

Source-destination discrimination on copy-move forgeries

Multimedia Tools and Applications, 2021
Since digital images are one of the most important carriers of information, their authenticity is quite important. There are miscellaneous forgery techniques for manipulating digital images, and one of those is copy-move forgery. Many forgery detection techniques have been developed for detection of copy-move forgery so far.
Emre Gürbüz, Güzin Ulutas, Mustafa Ulutas   +2 more
openaire   +1 more source

Adaptive matching for copy-move Forgery detection

2014 IEEE International Workshop on Information Forensics and Security (WIFS), 2014
The objective of copy-move forgery detection methods are to find copied regions within the same image. There are two main approaches to detect copy-move forgery: keypoint-based and block-based methods. Although the former is superior in terms of computational complexity, these methods neglect the smooth regions since they confine their search to ...
Mohsen Zandi, Ahmad Mahmoudi Aznaveh, Azadeh Mansouri   +2 more
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Copy move forgery detection based on LBP

2013 21st Signal Processing and Communications Applications Conference (SIU), 2013
Increase on the availability of the image editing tools makes it easy to create digital forgeries. More popular forgery in image manipulation is the copy move forgery where part of an image is copied into another location to hide an object. The methods that are used to detect the copy move forgery in images have a drawback. Length of the feature vector
Güzin Ulutas, Mustafa Ulutas, Vasif V. Nabiyev   +2 more
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Security of copy-move forgery detection techniques

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
Copy-move forgery is a specific form of image tampering, where a part of a digital image is copied and pasted into a different part of the same image. There are many copy-move forgery detection techniques, but their security has not been examined in detail. In this paper, we analyze the robustness and security of the detection techniques of Fridrich [1]
Hieu Cuong Nguyen, Stefan Katzenbeisser 0001   +1 more
openaire   +1 more source