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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...
ICCV
2007
IEEE
14 years 10 months ago
Event Detection in Crowded Videos
Real-world actions occur often in crowded, dynamic environments. This poses a difficult challenge for current approaches to video event detection because it is difficult to segmen...
Yan Ke, Rahul Sukthankar, Martial Hebert
MM
2004
ACM
248views Multimedia» more  MM 2004»
14 years 1 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
13 years 5 months ago
Single step evolution of robot controllers for sequential tasks
The generation of robot controllers for a task requiring a sequence of elementary behaviors is still a challenge. If these behaviors are known, intermediate steps can be given to ...
Stéphane Doncieux, Jean-Baptiste Mouret
SI3D
1999
ACM
14 years 12 days ago
GAPS: general and automatic polygonal simplification
We present a new approach for simplifying polygonal objects. Our method is general in that it works on models that contain both non-manifold geometry and surface attributes. It is...
Carl Erikson, Dinesh Manocha