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NAACL
2003
8 years 11 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classiļ¬cation of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
MOBISYS
2009
ACM
9 years 11 months ago
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Top end mobile phones include a number of specialized (e.g., accelerometer, compass, GPS) and general purpose sensors (e.g., microphone, camera) that enable new people-centric sen...
Hong Lu, Wei Pan, Nicholas D. Lane, Tanzeem Choudh...
CVPR
2007
IEEE
10 years 11 days ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson
TITS
2008
250views more  TITS 2008»
8 years 10 months ago
Learning, Modeling, and Classification of Vehicle Track Patterns from Live Video
This paper presents two different types of visual activity analysis modules based on vehicle tracking. The highway monitoring module accurately classifies vehicles into eight diffe...
Brendan Tran Morris, Mohan M. Trivedi
AVSS
2009
IEEE
8 years 11 months ago
Robust Vehicle Detection for Tracking in Highway Surveillance Videos Using Unsupervised Learning
This paper presents a novel approach to vehicle detection in highway surveillance videos. This method incorporates well-studied computer vision and machine learning techniques to ...
Birgi Tamersoy, Jake K. Aggarwal
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