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» Arguing from Experience to Classifying Noisy Data
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CIKM
2008
Springer
13 years 10 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
TSMC
2008
104views more  TSMC 2008»
13 years 8 months ago
Head Yaw Estimation From Asymmetry of Facial Appearance
This paper proposes a novel method to estimate the head yaw rotations based on the asymmetry of 2-D facial appearance. In traditional appearance-based pose estimation methods, feat...
Bingpeng Ma, Shiguang Shan, Xilin Chen, Wen Gao
TASLP
2008
154views more  TASLP 2008»
13 years 8 months ago
Capturing Local Variability for Speaker Normalization in Speech Recognition
The new model reduces the impact of local spectral and temporal variability by estimating a finite set of spectral and temporal warping factors which are applied to speech at the f...
Antonio Miguel, Eduardo Lleida, Richard Rose, Luis...
ICASSP
2011
IEEE
13 years 13 days ago
MCMC inference of the shape and variability of time-response signals
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...
CCGRID
2008
IEEE
14 years 3 months ago
Using Dynamic Condor-Based Services for Classifying Schizophrenia in Diffusion Tensor Images
— Diffusion Tensor Imaging (DTI) provides insight into the white matter of the human brain, which is affected by Schizophrenia. By comparing a patient group to a control group, t...
Simon Caton, Matthan Caan, Sílvia Delgado O...