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» Modeling affordances using Bayesian networks
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ICMLA
2007
14 years 11 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
FLAIRS
2000
14 years 11 months ago
Independence Semantics for BKBs
Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
Solomon Eyal Shimony, Eugene Santos Jr., Tzachi Ro...
ICPR
2010
IEEE
14 years 9 months ago
Data-Driven Lung Nodule Models for Robust Nodule Detection in Chest CT
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the...
Amal Farag, James Graham, Aly A. Farag
GAMESEC
2010
136views Game Theory» more  GAMESEC 2010»
14 years 8 months ago
Effective Multimodel Anomaly Detection Using Cooperative Negotiation
Abstract. Many computer protection tools incorporate learning techniques that build mathematical models to capture the characteristics of system's activity and then check whet...
Alberto Volpatto, Federico Maggi, Stefano Zanero
NIPS
2000
14 years 11 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick