Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Abstract. We consider the problem of learning stochastic tree languages, i.e. probability distributions over a set of trees T(F), from a sample of trees independently drawn accordi...
An online feature evaluation method for visual
object tracking is put forward in this paper. Firstly, a
combined feature set is built using color histogram (HC)
bins and gradien...
— In this paper, we introduce a novel Markov Chain (MC) representation aided Minimum Bit Error Rate (MBER) detection method that is applicable to an M-QAM modulated SDM/SDMA upli...
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...