Machine Learning Authentication
Machine Learning Authentication is a computational methodology that employs machine learning algorithms to verify the authenticity of meat products by distinguishing them from adulterated or mislabeled samples based on intrinsic biological or chemical signatures.
115
Publications
4.7K
Citations
475
Authors
204
Institutions
Publications per year
2017–2026
91
Parents
115
Deep learning in food authenticity: Recent advances and future trends
Zhuowen Deng, Tao Wang, Yun Zheng et al. · Trends in Food Science & Technology · 2024 · 149 citations
1–5 of 115
475
The University of Texas at San Antonio, United States
2 publications · 116 citations
2
h-index
Nanjing University of Science and Technology, China
2 publications · 112 citations
2
h-index
2
h-index
2
h-index
Central Electronics Engineering Research Institute, India
2 publications · 59 citations
2
h-index
1–5 of 475
204

King Saud University
Riyadh, Saudi Arabia
3 h-index
3 publications
227 citations
University of Connecticut
Storrs, United States
3 h-index
3 publications
136 citations

University of Trento
Trento, Italy
2 h-index
2 publications
40 citations
The University of Texas at San Antonio
San Antonio, United States
2 h-index
7 publications
201 citations
Vellore Institute of Technology University
Vellore, India
2 h-index
5 publications
325 citations
University College Dublin
Dublin, Ireland
2 h-index
5 publications
564 citations
Sichuan Agricultural University
Ya'an, China
2 h-index
2 publications
194 citations
Universidade Federal de Goiás
Goiânia, Brazil
2 h-index
3 publications
85 citations
1–8 of 204
4 publications · 320 citations
4
h-index
Repository · 4 publications · 73 citations
4
h-index
3 publications · 96 citations
3
h-index
2 publications · 82 citations
2
h-index
2 publications · 68 citations
2
h-index
1–5