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» Learning Models for Predicting Recognition Performance
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ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
15 years 21 days ago
Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
Daniel Munoz, Nicolas Vandapel, Martial Hebert
ICASSP
2011
IEEE
14 years 6 months ago
Generating compound words with high order n-gram information in large vocabulary speech recognition systems
In this work we concentrate on generating compound words with high order n-gram information for speech recognition. In most existing compound words generation methods, only bi-gra...
Jie Zhou, Qin Shi, Yong Qin
ICCV
2011
IEEE
14 years 3 months ago
Probabilistic Group-Level Motion Analysis and Scenario Recognition
This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative ...
Ming-Ching Chang, Nils Krahnstoever, Weina Ge
CHI
2010
ACM
15 years 9 months ago
Speech dasher: fast writing using speech and gaze
Speech Dasher allows writing using a combination of speech and a zooming interface. Users first speak what they want to write and then they navigate through the space of recognit...
Keith Vertanen, David J. C. MacKay
ICCV
2009
IEEE
16 years 8 months ago
Which Faces to Tag: Adding Prior Constraints into Active Learning
We introduce an algorithm that guides the user to tag faces in the best possible order during a face recognition assisted tagging scenario. In particular, we extend the active l...
Ashish Kapoor, Gang Hua, Amir Akbarzadeh and Simon...