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» Visual Exploration of High Dimensional Scalar Functions
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ICML
2010
IEEE
14 years 10 months ago
Deep networks for robust visual recognition
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
Yichuan Tang, Chris Eliasmith
ICPR
2006
IEEE
15 years 10 months ago
Object Tracking Using Globally Coordinated Nonlinear Manifolds
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
Che-Bin Liu, Ming-Hsuan Yang, Narendra Ahuja, Ruei...
KES
1998
Springer
15 years 1 months ago
Hidden partitioning of a visual feedback-based neuro-controller
Robotic controllers take advantage from neural network learning capabilities as long as the dimensionality of the problem is kept moderate. This paper explores the possibilities of...
Jean-Philippe Urban, Jean-Luc Buessler, Julien Gre...
81
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CGF
2007
165views more  CGF 2007»
14 years 9 months ago
Ray-Casted BlockMaps for Large Urban Models Visualization
We introduce a GPU-friendly technique that efficiently exploits the highly structured nature of urban environments to ensure rendering quality and interactive performance of city...
Paolo Cignoni, Marco Di Benedetto, Fabio Ganovelli...
MICCAI
2009
Springer
15 years 10 months ago
A Riemannian Framework for Orientation Distribution Function Computing
Compared with Diffusion Tensor Imaging (DTI), High Angular Resolution Imaging (HARDI) can better explore the complex microstructure of white matter. Orientation Distribution Functi...
Jian Cheng, Aurobrata Ghosh, Tianzi Jiang, Rachid ...