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» Combining VTS model compensation and support vector machines
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AVSS
2006
IEEE
14 years 8 days ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
14 years 3 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
BMCBI
2005
117views more  BMCBI 2005»
13 years 8 months ago
An SVM-based system for predicting protein subnuclear localizations
Background: The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computatio...
Zhengdeng Lei, Yang Dai
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
14 years 3 months ago
Towards robust place recognition for robot localization
— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of hi...
Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara C...
ICMI
2004
Springer
281views Biometrics» more  ICMI 2004»
14 years 1 months ago
Articulatory features for robust visual speech recognition
Visual information has been shown to improve the performance of speech recognition systems in noisy acoustic environments. However, most audio-visual speech recognizers rely on a ...
Kate Saenko, Trevor Darrell, James R. Glass