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DCC
2006
IEEE
16 years 1 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
ICPR
2006
IEEE
1292views computer vision» more  ICPR 2006»
16 years 3 months ago
Learning-Based License Plate Detection Using Global and Local Features
This paper proposes a license plate detection algorithm using both global statistical features and local Haar-like features. Classifiers using global statistical features are cons...
Huaifeng Zhang, Qiang Wu, Wenjing Jia, Xiangjian H...
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 9 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...
MICCAI
2005
Springer
15 years 7 months ago
Learning Best Features for Deformable Registration of MR Brains
Abstract. This paper presents a learning method to select best geometric features for deformable brain registration. Best geometric features are selected for each brain location, a...
Guorong Wu, Feihu Qi, Dinggang Shen
ICCV
2009
IEEE
1425views Computer Vision» more  ICCV 2009»
16 years 5 months ago
Fast Ray Features for Learning Irregular Shapes
We introduce a new class of image features, the Ray feature set, that consider image characteristics at distant contour points, capturing information which is difficult to repre...
Kevin Smith, Alan Carleton, Vincent Lepetit