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» Classification of symbolic objects: A lazy learning approach
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NIPS
2008
13 years 9 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
EDM
2010
152views Data Mining» more  EDM 2010»
13 years 9 months ago
Mining Students' Interaction Data from a System that Support Learning by Reflection
In this paper we utilising some popular educational data mining (EDM) methods to explore and mine educational data resulted from a system that supports reflection for learning call...
Rajibussalim
CVPR
2004
IEEE
14 years 9 months ago
A Model for Dynamic Shape and Its Applications
Variation in object shape is an important visual cue for deformable object recognition and classification. In this paper, we present an approach to model gradual changes in the ?-...
Che-Bin Liu, Narendra Ahuja
SOFTWARE
2002
13 years 7 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
ICINCO
2004
165views Robotics» more  ICINCO 2004»
13 years 9 months ago
Active Sensing Strategies for Robotic Platforms, with an Application in Vision-Based Gripping
: We present a vision-based robotic system which uses a combination of several active sensing strategies to grip a free-standing small target object with an initially unknown posit...
Benjamin Deutsch, Frank Deinzer, Matthias Zobel, J...