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» Unsupervised Learning of Visual Feature Hierarchies
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ICDAR
2007
IEEE
15 years 3 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
104
Voted
JAIR
2007
124views more  JAIR 2007»
14 years 9 months ago
Closed-Loop Learning of Visual Control Policies
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...
Sébastien Jodogne, Justus H. Piater
CVPR
2009
IEEE
1848views Computer Vision» more  CVPR 2009»
16 years 3 months ago
Moving Cast Shadow Detection using Physics-based Features
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...
Jia-Bin Huang and Chu-Song Chen
ICANN
2005
Springer
15 years 3 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
IJNS
2007
133views more  IJNS 2007»
14 years 9 months ago
Online Learning of Objects in a Biologically Motivated Visual Architecture
We present a biologically motivated architecture for object recognition that is capable of online learning of several objects based on interaction with a human teacher. The system...
Heiko Wersing, Stephan Kirstein, Michael Gött...