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CVPR
2011
IEEE
15 years 2 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
CVPR
2012
IEEE
13 years 9 months ago
Urban tribes: Analyzing group photos from a social perspective
The explosive growth in image sharing via social networks has produced exciting opportunities for the computer vision community in areas including face, text, product and scene re...
Ana C. Murillo, Iljung S. Kwak, Lubomir Bourdev, D...
PAMI
2007
92views more  PAMI 2007»
15 years 6 months ago
Modeling and Predicting Face Recognition System Performance Based on Analysis of Similarity Scores
—This paper presents methods of modeling and predicting face recognition (FR) system performance based on analysis of similarity scores. We define the performance of an FR system...
Peng Wang, Qiang Ji, James L. Wayman
DAGM
2003
Springer
15 years 11 months ago
Splines and Wavelets: New Perspectives for Pattern Recognition
We provide an overview of spline and wavelet techniques with an emphasis on applications in pattern recognition. The presentation is divided in three parts. In the first one, we ar...
Michael Unser
MVA
2000
172views Computer Vision» more  MVA 2000»
15 years 8 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi