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ESANN
2007
13 years 11 months ago
Markovian blind separation of non-stationary temporally correlated sources
In a previous work, we developed a quasi-efficient maximum likelihood approach for blindly separating stationary, temporally correlated sources modeled by Markov processes. In this...
Rima Guidara, Shahram Hosseini, Yannick Deville
ICCV
2011
IEEE
12 years 9 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
AAAI
2000
13 years 11 months ago
Restricted Bayes Optimal Classifiers
We introduce the notion of restricted Bayes optimal classifiers. These classifiers attempt to combine the flexibility of the generative approach to classification with the high ac...
Simon Tong, Daphne Koller
JMM2
2007
148views more  JMM2 2007»
13 years 9 months ago
Object Segmentation Using Background Modelling and Cascaded Change Detection
— The automatic extraction and analysis of visual information is becoming generalised. The first step in this processing chain is usually separating or segmenting the captured v...
Luís Filipe Teixeira, Jaime S. Cardoso, Lu&...
ICCS
2004
Springer
14 years 3 months ago
Developing a Data Driven System for Computational Neuroscience
Abstract. A data driven system implies the need to integrate data acquisition and signal processing into the same system that will interact with this information. This can be done ...
Ross Snider, Yongming Zhu