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ICML
2008
IEEE
14 years 11 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
TOG
2008
98views more  TOG 2008»
13 years 10 months ago
Upright orientation of man-made objects
Humans usually associate an upright orientation with objects, placing them in a way that they are most commonly seen in our surroundings. While it is an open challenge to recover ...
Hongbo Fu, Daniel Cohen-Or, Gideon Dror, Alla Shef...
CVPR
2012
IEEE
12 years 25 days ago
Discrete texture traces: Topological representation of geometric context
Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
Jan Ernst, Maneesh Kumar Singh, Visvanathan Ramesh
CVPR
2007
IEEE
15 years 12 days ago
An Exemplar Model for Learning Object Classes
We introduce an exemplar model that can learn and generate a region of interest around class instances in a training set, given only a set of images containing the visual class. T...
Ondrej Chum, Andrew Zisserman
ECTEL
2007
Springer
14 years 4 months ago
Using MotSaRT to Support On-Line Teachers in Student Motivation
Motivation to learn is affected by a student’s self-efficacy, goal orientation, locus of control and perceived task difficulty. In the classroom, teachers know how to motivate th...
Teresa Hurley, Stephan Weibelzahl