Forgery Classification is a methodological framework within forgery detection that systematically differentiates forged from authentic instances by analyzing distinguishing anomalies in content, style, or structure according to predefined criteria.
70
Publications
3.2K
Citations
246
Authors
116
Institutions
Publications per year
2017–2026
46
Parents
Publications
70
Physics-motivated features for distinguishing photographic images and computer graphics
Tian-Tsong Ng, Shih‐Fu Chang, Jessie Hsu et al. · 2005 · 184 citations
Hierarchical Fine-Grained Image Forgery Detection and Localization
Xiao Guo, Xiaohong Liu, Zhiyuan Ren et al. · 2023 · 165 citations
1–5 of 70
Authors
246
- RS
4
h-index
- FB
3
h-index
- TL
3
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- MA
2
h-index
- UP
2
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1–5 of 246
Institutions
116
École de Technologie Supérieure
Montreal, Canada
4 h-index
8 publications
305 citations
Amity University
Noida, India
3 h-index
11 publications
149 citations
Chandigarh University
Mohali, India
2 h-index
2 publications
41 citations
Shenzhen University
Shenzhen, China
2 h-index
2 publications
79 citations
Pontifícia Universidade Católica do Paraná
Curitiba, Brazil
2 h-index
5 publications
268 citations
Sun Yat-sen University
Guangzhou, China
2 h-index
6 publications
282 citations
Panjab University
Chandigarh, India
2 h-index
4 publications
164 citations
University of Malaya
Kuala Lumpur, Malaysia
2 h-index
2 publications
32 citations
1–8 of 116
Venues
- Multimedia Tools and Applications
6 publications · 197 citations
6
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- IEEE Transactions on Information Forensics and Security
2 publications · 66 citations
2
h-index
- IET Biometrics
BMT · 2 publications · 65 citations
2
h-index
- IEEE Transactions on Image Processing
1 publications · 44 citations
1
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- International Journal of Security and Its Applications
IJSIA · 1 publications · 10 citations
1
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1–5