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» Learning Image Components for Object Recognition
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CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
16 years 10 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...
ICPR
2008
IEEE
15 years 9 months ago
A 2D model for face superresolution
Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
B. G. Vijay Kumar, Rangarajan Aravind
ICPR
2002
IEEE
16 years 3 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
WAPCV
2007
Springer
15 years 9 months ago
Reinforcement Learning for Decision Making in Sequential Visual Attention
The innovation of this work is the provision of a system that learns visual encodings of attention patterns and that enables sequential attention for object detection in real world...
Lucas Paletta, Gerald Fritz
CVPR
2003
IEEE
16 years 4 months ago
Video-Based Face Recognition Using Probabilistic Appearance Manifolds
This paper presents a novel method to model and recognize human faces in video sequences. Each registered person is represented by a low-dimensional appearance manifold in the amb...
Kuang-Chih Lee, Jeffrey Ho, Ming-Hsuan Yang, David...