Results 121 to 130 of about 23,633 (272)

SPA-Net: A Deep Learning Approach Enhanced Using a Span-Partial Structure and Attention Mechanism for Image Copy-Move Forgery Detection. [PDF]

Sensors (Basel), 2023
Zhao K, Yuan X, Xie Z, Xiang Y, Huang G, Feng L.   +5 more
europepmc   +1 more source

Video forgery detection

, 2016
Digital image and videos cannot be taken as authentic evidences, since their integrity is no longer trustworthy. Because of the uniqueness and peculiarities of video signals with respect to images, there are wider ranges of possible alterations that can be applied on video signals.
openaire   +1 more source

Dual-Module Architecture for Robust Image Forgery Segmentation and Classification Toward Cyber Fraud Investigation

Applied Sciences
This study presents a dual-module architecture for image forgery detection in the context of cyber fraud investigation, designed to provide interpretable and court-admissible forensic evidence.
Donghwan Kim, Hansoo Kim
doaj   +1 more source

Learning to Discover Forgery Cues for Face Forgery Detection

IEEE Transactions on Information Forensics and Security
TIFS ...
Jiahe Tian, Peng Chen, Cai Yu, Xiaomeng Fu, Xi Wang, Jiao Dai, Jizhong Han   +6 more
openaire   +2 more sources

ID3: Identity-Driven Learning Based on 3D Reconstruction and Frame-Level Residual Enhancement for Deepfakes Detection

IET Biometrics
With the rapid advancement of face manipulation technology, various forged videos of celebrities and politicians have appeared and cause pernicious social impact. In this light, forge video detection becomes a research hot spot recently.
Hui Ma, Jin Zhang, Xihong Chen, Wenhao Chu, Jiabao Guo, Junze Zheng, Liying Yang, Yanyan Liang   +7 more
doaj   +1 more source

Enhancing Deepfake Detection With Diversified Self-Blending Images and Residuals

IEEE Access
The advancement of deep forgery technology has significantly impacted the credibility of media content, making the detection of deep forgeries crucial for ensuring media security.
Qingtong Liu, Ziyu Xue, Haitao Liu, Jing Liu   +3 more
doaj   +1 more source

Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation. [PDF]

Multimed Tools Appl, 2023
Sharma P, Kumar M, Kumar M, Sharma H.
europepmc   +1 more source

Introducing AI & Innovation

AI &Innovation, EarlyView.
Mirko Farina, Xiao Yu, Rongrong Ji, Chen Jin, Vincent Blok, Paolo Ciancarini, Ngcaweni Busani, Witold Pedrycz   +7 more
wiley   +1 more source

CNN-Keypoint Based Two-Stage Hybrid Approach for Copy-Move Forgery Detection

IEEE Access
Authenticating digital images poses a significant challenge due to the widespread use of image forgery techniques, including copy-move forgery. Copy-move forgery involves copying and pasting portions of an image within the same image while applying ...
Anjali Diwan, Anil K. Roy
doaj   +1 more source

Forgery Detection in Digital Images by Multi-Scale Noise Estimation. [PDF]

J Imaging, 2021
Gardella M, Musé P, Morel JM, Colom M.
europepmc   +1 more source