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» The Dark Side of Object Learning: Learning Objects
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120
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SIGIR
2008
ACM
15 years 3 months ago
Novelty and diversity in information retrieval evaluation
Evaluation measures act as objective functions to be optimized by information retrieval systems. Such objective functions must accurately reflect user requirements, particularly w...
Charles L. A. Clarke, Maheedhar Kolla, Gordon V. C...
134
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PRL
2007
100views more  PRL 2007»
15 years 3 months ago
Visible models for interactive pattern recognition
The bottleneck in interactive visual classification is the exchange of information between human and machine. We introduce the concept of the visible model, which is an ion of an ...
Jie Zou, George Nagy
127
Voted
ICVS
2009
Springer
15 years 1 months ago
Boosting with a Joint Feature Pool from Different Sensors
This paper introduces a new way to apply boosting to a joint feature pool from different sensors, namely 3D range data and color vision. The combination of sensors strengthens the ...
Dominik Alexander Klein, Dirk Schulz, Simone Frint...
142
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CORR
2010
Springer
237views Education» more  CORR 2010»
15 years 1 months ago
Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss
The problem of identifying the 3D pose of a known object from a given 2D image has important applications in Computer Vision ranging from robotic vision to image analysis. Our pro...
Srimal Jayawardena, Marcus Hutter, Nathan Brewer
128
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CORR
2011
Springer
127views Education» more  CORR 2011»
14 years 7 months ago
Generalized Boosting Algorithms for Convex Optimization
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
Alexander Grubb, J. Andrew Bagnell