Cargando…
A Survey of Deep Learning-Based Source Image Forensics
Image source forensics is widely considered as one of the most effective ways to verify in a blind way digital image authenticity and integrity. In the last few years, many researchers have applied data-driven approaches to this task, inspired by the excellent performance obtained by those technique...
Autores principales: | Yang, Pengpeng, Baracchi, Daniele, Ni, Rongrong, Zhao, Yao, Argenti, Fabrizio, Piva, Alessandro |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321025/ https://www.ncbi.nlm.nih.gov/pubmed/34460606 http://dx.doi.org/10.3390/jimaging6030009 |
Ejemplares similares
-
A New Dataset for Source Identification of High Dynamic Range Images
por: Al Shaya, Omar, et al.
Publicado: (2018) -
A Comprehensive Review of Deep-Learning-Based Methods for Image Forensics
por: Castillo Camacho, Ivan, et al.
Publicado: (2021) -
Trends in forensic microbiology: From classical methods to deep learning
por: Yuan, Huiya, et al.
Publicado: (2023) -
Copy-Move Forgery Detection (CMFD) Using Deep Learning for Image and Video Forensics
por: Rodriguez-Ortega, Yohanna, et al.
Publicado: (2021) -
An annotated image dataset of medically and forensically important flies for deep learning model training
por: Ong, Song-Quan, et al.
Publicado: (2022)