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» Unsupervised Learning Using MML
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NIPS
2004
13 years 10 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
CORR
2010
Springer
185views Education» more  CORR 2010»
13 years 5 months ago
Analysing the behaviour of robot teams through relational sequential pattern mining
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
Grazia Bombini, Raquel Ros, Stefano Ferilli, Ramon...
ICCV
2007
IEEE
14 years 10 months ago
Hierarchical Semantics of Objects (hSOs)
A successful representation of objects in the literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different p...
Devi Parikh, Tsuhan Chen
ECCV
2008
Springer
14 years 10 months ago
Multi-camera Tracking and Atypical Motion Detection with Behavioral Maps
Abstract. We introduce a novel behavioral model to describe pedestrians motions, which is able to capture sophisticated motion patterns resulting from the mixture of different cate...
Jérôme Berclaz, François Fleur...
ECCV
2004
Springer
14 years 10 months ago
A Visual Category Filter for Google Images
We extend the constellation model to include heterogeneous parts which may represent either the appearance or the geometry of a region of the object. The parts and their spatial co...
Robert Fergus, Pietro Perona, Andrew Zisserman