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JCDL
2006
ACM
92views Education» more  JCDL 2006»
14 years 3 months ago
Probabilistic, object-oriented logics for annotation-based retrieval in digital libraries
In this paper we introduce POLAR, a probabilistic objectoriented logical framework for annotation-based information retrieval. In POLAR, the knowledge about digital objects, annot...
Ingo Frommholz, Norbert Fuhr
AVSS
2006
IEEE
14 years 25 days ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
FUIN
2008
108views more  FUIN 2008»
13 years 7 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
IROS
2007
IEEE
95views Robotics» more  IROS 2007»
14 years 3 months ago
Modeling affordances using Bayesian networks
— Affordances represent the behavior of objects in terms of the robot’s motor and perceptual skills. This type of knowledge plays a crucial role in developmental robotic system...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
TSP
2010
13 years 3 months ago
Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR
In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multi-target state estimat...
Daniel Clark, Branko Ristic, Ba-Ngu Vo, Ba-Tuong V...