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» Preference-based learning to rank
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100
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CVPR
2010
IEEE
15 years 5 months ago
Object Recognition as Ranking Holistic Figure-Ground Hypotheses
We present an approach to visual object-class recognition and segmentation based on a pipeline that combines multiple, holistic figure-ground hypotheses generated in a bottom-up,...
Fuxin Li, JoãCarreira, Cristian Sminchisescu
105
Voted
PICS
2003
15 years 1 months ago
Eye Tracking Observers During Rank Order, Paired Comparison, and Graphical Rating Tasks
In studying image quality and image preference it is necessary to collect psychophysical data. A variety of methods are used to arrive at interval scale values which indicate the ...
Jason S. Babcock, Jeff B. Pelz, Mark D. Fairchild
86
Voted
CORR
2010
Springer
140views Education» more  CORR 2010»
15 years 19 days ago
Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques
We propose a mid-level image segmentation framework that combines multiple figure-ground hypothesis (FG) constrained at different locations and scales, into interpretations that t...
João Carreira, Adrian Ion, Cristian Sminchi...
CVPR
2009
IEEE
15 years 4 months ago
Learning to associate: HybridBoosted multi-target tracker for crowded scene
We propose a learning-based hierarchical approach of multi-target tracking from a single camera by progressively associating detection responses into longer and longer track fragm...
Yuan Li, Chang Huang, Ram Nevatia
NAACL
1994
15 years 1 months ago
Learning from Relevant Documents in Large Scale Routing Retrieval
The normal practice of selecting relevant documents for training routing queries is to either use all relevants or the 'best n' of them after a (retrieval) ranking opera...
K. L. Kwok, Laszlo Grunfeld