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» Arguing from Experience to Classifying Noisy Data
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CIKM
2008
Springer
15 years 3 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»
15 years 1 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»
15 years 1 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
14 years 5 months 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
15 years 8 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...