Skip to search formSkip to main contentSkip to account menu

Bayesian network

Known as: Bayesian belief network, Belief networks, Bayes net 
A Bayesian network, Bayes network, belief network, Bayes(ian) model or probabilistic directed acyclic graphical model is a probabilistic graphical… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2013
Highly Cited
2013
Human’s non-verbal behavior may convey different meanings. They can reflect one’s emotional states, communicative intentions but… 
Highly Cited
2010
Highly Cited
2010
Cell segmentation in microscopy imagery is essential for many bioimage applications such as cell tracking. To segment cells from… 
Highly Cited
2004
Highly Cited
2004
In this paper, we introduce new algorithms for automatic tracking of multiaspect targets in cluttered image sequences. We depart… 
Highly Cited
2004
Highly Cited
2004
To improve the understanding of effects of environmental factors on spawner-to-recruit survival rates of pink salmon… 
Highly Cited
2001
Highly Cited
2001
We present near-IR (J and Ks) number counts and colors of galaxies detected in deep VLT-ISAAC images centered on the Chandra Deep… 
Highly Cited
1998
Highly Cited
1998
For pt.I see ibid., p.1431-45 (1998). The authors present Gibbs-Markov random field (GMRF) models as a powerful and robust… 
Highly Cited
1997
Highly Cited
1997
When performing regression or classification, we are interested in the conditional probability distribution for an outcome or… 
Highly Cited
1995
Highly Cited
1995
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1992
Highly Cited
1984
Highly Cited
1984
  • M. Gauvrit
  • 1984
  • Corpus ID: 20084986