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ICML
2010
IEEE
15 years 28 days ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICIP
2007
IEEE
16 years 1 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
CVPR
2010
IEEE
15 years 8 months ago
An Object-Dependent Hand Pose Prior from Sparse Training Data
In this paper, we propose a prior for hand pose estimation that integrates the direct relation between a manipulating hand and a 3d object. This is of particular interest for a va...
Henning Hamer, Juergen Gall, Thibaut Weise, Luc Va...
ICVGIP
2004
15 years 1 months ago
Learning Layered Pictorial Structures from Video
We propose a new unsupervised learning method to obtain a layered pictorial structure (LPS) representation of an articulated object from video sequences. It will be seen that this...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
ICANN
2011
Springer
14 years 3 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes