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TSMC
1998
91views more  TSMC 1998»
13 years 8 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...
CVPR
2010
IEEE
14 years 5 months ago
Cascade Object Detection with Deformable Part Models
We describe a general method for building cascade classifiers from part-based deformable models such as pictorial structures. We focus primarily on the case of star-structured mod...
Pedro Felzenszwalb, Ross Girshick, David McAlleste...
CVPR
1999
IEEE
14 years 11 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
BMCBI
2005
161views more  BMCBI 2005»
13 years 8 months ago
Non-linear mapping for exploratory data analysis in functional genomics
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Francisco Azuaje, Haiying Wang, Alban Chesneau
SDM
2010
SIAM
158views Data Mining» more  SDM 2010»
13 years 10 months ago
On the Use of Combining Rules in Relational Probability Trees
A relational probability tree (RPT) is a type of decision tree that can be used for probabilistic classification of instances with a relational structure. Each leaf of an RPT cont...
Daan Fierens