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CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
CVPR
2006
IEEE
14 years 10 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ICB
2007
Springer
176views Biometrics» more  ICB 2007»
14 years 13 days ago
A Novel Null Space-Based Kernel Discriminant Analysis for Face Recognition
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
Tuo Zhao, Zhizheng Liang, David Zhang, Yahui Liu
CVPR
2009
IEEE
15 years 3 months ago
Learning query-dependent prefilters for scalable image retrieval
We describe an algorithm for similar-image search which is designed to be efficient for extremely large collections of images. For each query, a small response set is selected by...
Lorenzo Torresani (Dartmouth College), Martin Szum...
ICML
2009
IEEE
14 years 9 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...