Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
We propose a novel nonparametric Bayesian model, Dual Hierarchical Dirichlet Processes (Dual-HDP), for trajectory analysis and semantic region modeling in surveillance settings, i...
Xiaogang Wang, Keng Teck Ma, Gee Wah Ng, W. Eric L...
In this paper, we propose a new application of Bayesian language model based on Pitman-Yor process for information retrieval. This model is a generalization of the Dirichlet distr...
Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...