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CVPR
1999
IEEE
16 years 6 months ago
Implicit Representation and Scene Reconstruction from Probability Density Functions
A technique is presented for representing linear features as probability density functions in two or three dimensions. Three chief advantages of this approach are (1) a unified re...
Steven M. Seitz, P. Anandan
ICICIC
2006
IEEE
15 years 10 months ago
Visibility Estimation in Foggy Conditions by In-Vehicle Camera and Radar
We propose a method of judging fog density by using invehicle camera images and millimeter-wave (mm-W) radar data. This method determines fog density by evaluating both the visibi...
Kenji Mori, Terutoshi Kato, Tomokazu Takahashi, Ic...
DATE
2006
IEEE
111views Hardware» more  DATE 2006»
15 years 10 months ago
Extraction of defect density and size distributions from wafer sort test results
Defect density and defect size distributions (DDSDs) are key parameters used in IC yield loss predictions. Traditionally, memories and specialized test structures have been used t...
Jeffrey E. Nelson, Thomas Zanon, Rao Desineni, Jas...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 5 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
IJON
2007
118views more  IJON 2007»
15 years 4 months ago
CATS benchmark time series prediction by Kalman smoother with cross-validated noise density
This article presents the winning solution to the CATS time series prediction competition. The solution is based on classical optimal linear estimation theory. The proposed method...
Simo Särkkä, Aki Vehtari, Jouko Lampinen