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» Learning from Multiple Annotators with Gaussian Processes
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CVPR
2011
IEEE
13 years 2 months ago
FlowBoost - Appearance Learning from Sparsely Annotated Video
We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists...
Karim Ali, Francois Fleuret, David Hasler
ICC
2007
IEEE
14 years 1 months ago
UWB Impulse Radio Receivers Derived from a Gaussian Mixture Interference Model
— One of the main concerns in ultra wide band (UWB) impulse radio (IR) technology is the presence of severe multiple access interference (MAI). Efficient receivers should theref...
Tomaso Erseghe, Valentina Cellini, Gabriele Don&aa...
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 8 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ICGI
2004
Springer
14 years 2 days ago
Learning Node Selecting Tree Transducer from Completely Annotated Examples
Abstract. A base problem in Web information extraction is to find appropriate queries for informative nodes in trees. We propose to learn queries for nodes in trees automatically ...
Julien Carme, Aurélien Lemay, Joachim Niehr...

Publication
226views
12 years 5 months ago
Modelling Multi-object Activity by Gaussian Processes
We present a new approach for activity modelling and anomaly detection based on non-parametric Gaussian Process (GP) models. Specifically, GP regression models are formulated to l...
Chen Change Loy, Tao Xiang, Shaogang Gong