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IJCAI
1989
13 years 8 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
CVPR
2006
IEEE
14 years 9 months ago
When Fisher meets Fukunaga-Koontz: A New Look at Linear Discriminants
The Fisher Linear Discriminant (FLD) is commonly used in pattern recognition. It finds a linear subspace that maximally separates class patterns according to Fisher's Criteri...
Sheng Zhang, Terence Sim
ICDAR
2007
IEEE
14 years 2 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
AVBPA
2001
Springer
145views Biometrics» more  AVBPA 2001»
14 years 5 days ago
Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions
In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training samples for each p...
Carlos E. Thomaz, Duncan Fyfe Gillies, Raul Queiro...
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
14 years 27 days ago
Visual Analysis of the Use of Mixture Covariance Matrices in Face Recognition
The quadratic discriminant (QD) classifier has proved to be simple and effective in many pattern recognition problems. However, it requires the computation of the inverse of the sa...
Carlos E. Thomaz, Duncan Fyfe Gillies