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» Learning the Relative Importance of Features in Image Data
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VIS
2008
IEEE
120views Visualization» more  VIS 2008»
16 years 5 months ago
Size-based Transfer Functions: A New Volume Exploration Technique
The visualization of complex 3D images remains a challenge, a fact that is magnified by the difficulty to classify or segment volume data. In this paper, we introduce size-based tr...
Carlos D. Correa, Kwan-Liu Ma
ICIAR
2009
Springer
15 years 2 months ago
A Robust Modular Wavelet Network Based Symbol Classifier
This paper presents a robust automatic shape classifier using modular wavelet networks (MWNs). A shape descriptor is constructed based on a combination of global geometric features...
Akshaya Kumar Mishra, Paul W. Fieguth, David A. Cl...
RT
2001
Springer
15 years 8 months ago
Image-Based Reconstruction of Spatially Varying Materials
The measurement of accurate material properties is an important step towards photorealistic rendering. Many real-world objects are composed of a number of materials that often show...
Hendrik P. A. Lensch, Michael Goesele, Jan Kautz, ...
CVPR
2008
IEEE
16 years 6 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
ECCV
2008
Springer
16 years 6 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...