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» Learning Models for Object Recognition
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NIPS
2008
15 years 5 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
IBPRIA
2009
Springer
15 years 8 months ago
Score Fusion by Maximizing the Area under the ROC Curve
Information fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the paramete...
Mauricio Villegas, Roberto Paredes
166
Voted
ACL
2006
15 years 5 months ago
Combining Statistical and Knowledge-Based Spoken Language Understanding in Conditional Models
Spoken Language Understanding (SLU) addresses the problem of extracting semantic meaning conveyed in an utterance. The traditional knowledge-based approach to this problem is very...
Ye-Yi Wang, Alex Acero, Milind Mahajan, John Lee
124
Voted
ICRA
2005
IEEE
105views Robotics» more  ICRA 2005»
15 years 9 months ago
Learning Activity-Based Ground Models from a Moving Helicopter Platform
— We present a method for learning activity-based ground models based on a multiple particle filter approach to motion tracking in video acquired from a moving aerial platform. ...
Andrew Lookingbill, David Lieb, David Stavens, Seb...
131
Voted
VISAPP
2007
15 years 4 months ago
Extraction of multi-modal object representations in a robot vision system
We introduce one module in a cognitive system that learns the shape of objects by active exploration. More specifically, we propose a feature tracking scheme that makes use of the...
Nicolas Pugeault, Emre Baseski, Dirk Kraft, Floren...