Cargando…
Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation
The digital image proves critical evidence in the fields like forensic investigation, criminal investigation, intelligence systems, medical imaging, insurance claims, and journalism to name a few. Images are an authentic source of information on the internet and social media. But, using easily avail...
Autores principales: | Sharma, Preeti, Kumar, Manoj, Sharma, Hitesh |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525232/ https://www.ncbi.nlm.nih.gov/pubmed/36213342 http://dx.doi.org/10.1007/s11042-022-13808-w |
Ejemplares similares
-
Copy-Move Forgery Detection (CMFD) Using Deep Learning for Image and Video Forensics
por: Rodriguez-Ortega, Yohanna, et al.
Publicado: (2021) -
Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection
por: Krishnaraj, N., et al.
Publicado: (2022) -
Exposing Image Forgery by Detecting Consistency of Shadow
por: Ke, Yongzhen, et al.
Publicado: (2014) -
Retracted: Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection
por: Intelligence and Neuroscience, Computational
Publicado: (2023) -
Region Duplication Forgery Detection Technique Based on SURF and HAC
por: Mishra, Parul, et al.
Publicado: (2013)