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» Hierarchical Hidden Markov Models for Information Extraction
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AAAI
2004
15 years 2 months ago
Learning and Inferring Transportation Routines
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Lin Liao, Dieter Fox, Henry A. Kautz
PCM
2001
Springer
150views Multimedia» more  PCM 2001»
15 years 6 months ago
Unsupervised Analysis of Human Gestures
Recognition of human gestures is important for analysis and indexing of video. To recognize human gestures on video, generally a large number of training examples for each individu...
Tianshu Wang, Heung-Yeung Shum, Ying-Qing Xu, Nann...
VLSISP
2010
191views more  VLSISP 2010»
14 years 8 months ago
Sign Language Phoneme Transcription with Rule-based Hand Trajectory Segmentation
A common approach to extract phonemes of sign language is to use an unsupervised clustering algorithm to group the sign segments. However, simple clustering algorithms based on dis...
W. W. Kong, Surendra Ranganath
FAST
2010
15 years 3 months ago
Discovery of Application Workloads from Network File Traces
An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level he...
Neeraja J. Yadwadkar, Chiranjib Bhattacharyya, K. ...
BMCBI
2008
155views more  BMCBI 2008»
15 years 1 months ago
Prediction of regulatory elements in mammalian genomes using chromatin signatures
Background: Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, pro...
Kyoung-Jae Won, Iouri Chepelev, Bing Ren, Wei Wang