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BMCBI
2010
229views more  BMCBI 2010»
13 years 9 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
CVPR
2009
IEEE
15 years 4 months ago
Unsupervised Learning of Hierarchical Spatial Structures In Images
The visual world demonstrates organized spatial patterns, among objects or regions in a scene, object-parts in an object, and low-level features in object-parts. These classes o...
Devi Parikh (Carnegie Mellon University), C. Lawre...
ICIP
2000
IEEE
14 years 10 months ago
Combined Dynamic Tracking and Recognition of Curves with Application to Road Detection
We present an algorithm that extracts the largest shape within a specificclass, starting from a set of image edgels. The algorithm inherits the Best-First Segmentation approach [jp...
Frederic Guichard, Jean-Philippe Tarel
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
14 years 3 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
SAC
2006
ACM
14 years 3 months ago
Trust-decisions on the base of maximal information of recommended direct-trust
Nowadays the concept of trust in computer communications starts to get more and more popular. While the idea of trust in human interaction seems to be obvious and understandable i...
Uwe Roth, Volker Fusenig