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Face and Expression Recognition
TopicLeading institutions, researchers & key papers
This cluster of papers focuses on the application of various machine learning and dimensionality reduction techniques to the field of face recognition. It covers topics such as feature selection, support vector machines, ensemble methods, local binary patterns, non-negative matrix factorization, spectral clustering, Laplacian eigenmaps, and sparse representation in the context of face recognition.
177
Works
IDs:OpenAlex
How has Face and Expression Recognition's publication output changed over time?
ScholarIQpublication output · 1998–2021
Output declined50% over the shown period — from 2 works in 1998 to 1 in 2021.
2
2
1
1
1
2
2
3
1
199820022005200620102011201720202021
What are the most-cited papers on Face and Expression Recognition?
ScholarIQmost cited works
Regularization Paths for Generalized Linear Models via Coordinate Descent
Jerome H. Friedman, Trevor Hastie, Robert Tibshirani
S167961193. 201017,408 CitationsOPEN ACCESS
Linear discriminant analysis: A detailed tutorial
Alaa Tharwat, Tarek Gaber, Abdelhameed Ibrahim, Aboul Ella Hassanien
S176303223. 20171,078 CitationsOPEN ACCESS
Selecting critical features for data classification based on machine learning methods
Rung-Ching Chen, Christine Dewi, Su-Wen Huang, Rezzy Eko Caraka
S2737955091. 2020988 CitationsOPEN ACCESS
The FERET evaluation methodology for face-recognition algorithms
P. Jonathon Phillips, Hyeonjoon Moon, Patrick J. Rauss, Syed A. Rizvi
2002590 Citations
Where is Face and Expression Recognition research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
S16796119317,408
S1763032231,078
S2737955091988
S414566310
S4210191458280
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Face and Expression Recognition is open access?
ScholarIQopen access share
40%OPEN ACCESS
Gold
33%
Green
7%
Hybrid
0%
Bronze
0%
Closed
60%
Related on ScholarIQ
Regularization Paths for Generalized Linear Models via Coordinate Descent
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Online Learning for Matrix Factorization and Sparse Coding
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Sparse Representation for Computer Vision and Pattern Recognition
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Linear discriminant analysis: A detailed tutorial
Paper
Selecting critical features for data classification based on machine learning methods
Paper
Co-regularized Multi-view Spectral Clustering
Paper