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ICIP
2007
IEEE
14 years 9 months ago
Large Scale Learning of Active Shape Models
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...
Atul Kanaujia, Dimitris N. Metaxas
ICASSP
2011
IEEE
12 years 11 months ago
Similarity learning for semi-supervised multi-class boosting
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the e...
Q. Y. Wang, Pong Chi Yuen, Guo-Can Feng
ICANN
2011
Springer
12 years 11 months ago
Semi-supervised Learning for WLAN Positioning
Currently the most accurate WLAN positioning systems are based on the fingerprinting approach, where a “radio map” is constructed by modeling how the signal strength measureme...
Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
TCSV
2008
313views more  TCSV 2008»
13 years 7 months ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
JNS
2010
98views more  JNS 2010»
13 years 6 months ago
Analysis of a General Family of Regularized Navier-Stokes and MHD Models
ABSTRACT. We consider a general family of regularized Navier-Stokes and Magnetohydrodynamics (MHD) models on n-dimensional smooth compact Riemannian manifolds with or without bound...
Michael Holst, Evelyn Lunasin, Gantumur Tsogtgerel