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» Hierarchical Hidden Markov Models for Information Extraction
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FLAIRS
2010
15 years 2 months ago
Learning to Identify and Track Imaginary Objects Implied by Gestures
A vision-based machine learner is presented that learns characteristic hand and object movement patterns for using certain objects, and uses this information to recreate the "...
Andreya Piplica, Alexandra Olivier, Allison Petros...
JCST
2008
138views more  JCST 2008»
14 years 11 months ago
Predicting Chinese Abbreviations from Definitions: An Empirical Learning Approach Using Support Vector Regression
In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an em...
Xu Sun, Houfeng Wang, Bo Wang 0003
BMCBI
2004
108views more  BMCBI 2004»
14 years 11 months ago
Enhanced protein domain discovery using taxonomy
Background: It is well known that different species have different protein domain repertoires, and indeed that some protein domains are kingdom specific. This information has not ...
Lachlan James M. Coin, Alex Bateman, Richard Durbi...
ICASSP
2011
IEEE
14 years 3 months ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
98
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ICIP
2000
IEEE
15 years 4 months ago
Multiscale Texture Segmentation Using Hybrid Contextual Labeling Tree
Wavelet-domain hidden Markov tree (HMT) model has been recently proposed and applied to image processing, e.g., image segmentation. A new multiscale image segmentation method, cal...
Guoliang Fan, Xiang-Gen Xia