Results 91 to 100 of about 13,849 (178)

Rethinking VLMs for Image Forgery Detection and Localization

CoRR
8pages
Shaofeng Guo, Jiequan Cui, Richang Hong
openaire   +2 more sources

Analysis of Copy-move Manipulation in Digital Images using Scale Invariant Feature Transform (SIFT) and SVD-matching Methods

Journal of Applied Informatics and Computing
In recent years, more and more data has been created in digital form, allowing for easier control over storage and manipulation thanks to technological advancements.
Muhamad Masjun Efendi, Nukman Nukman
doaj   +1 more source

Medical Image Forgery Detection

, 2022
Currently, the majority of businesses and organizations rely on internet services because of the improvements in technology and how simple they are to acquire and use. In the medical sector, digital photographs have also gained more significance than before.
openaire   +1 more source

Image Forgery Analyse and Detection

International Journal of Computer Science and Engineering, 2021
Alhussain Akoum, Samia Bahlak, Nagham Abou Daher   +2 more
openaire   +1 more source

A hybrid model for image forgery detection using deep learning with block and keypoint methods. [PDF]

Sci Rep
Mehrjardi FZ, Zarchi MS.
europepmc   +1 more source

Hybrid framework for image forgery detection and robustness against adversarial attacks using vision transformer and SVM. [PDF]

Sci Rep
Abdelmaksoud M, Youssef B, Wassif K, A El-Khoribi R.   +3 more
europepmc   +1 more source

Digital image forgery detection using JPEG features and local noise discrepancies. [PDF]

ScientificWorldJournal, 2014
Liu B, Pun CM, Yuan XC.
europepmc   +1 more source

DeepForgeryNet: a hybrid CNN-LSTM and transfer learning framework for robust image forgery and deepfake detection. [PDF]

Front Artif Intell
Sardhara A, Vekariya V, Pathak AR, Dash S.   +3 more
europepmc   +1 more source

Robust Detection and Localization of Image Copy-Move Forgery Using Multi-Feature Fusion. [PDF]

J Imaging
Lu K, Zhang Q.
europepmc   +1 more source

Multiple contexts and frequencies aggregation network for deepfake detection. [PDF]

PLoS One
Li Z, Tang W, Gao S, Wang Y, Wang S.
europepmc   +1 more source