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» Patient Fall Detection using Support Vector Machines
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NIPS
2001
13 years 9 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
NIPS
2004
13 years 9 months ago
An Auditory Paradigm for Brain-Computer Interfaces
Motivated by the particular problems involved in communicating with "locked-in" paralysed patients, we aim to develop a braincomputer interface that uses auditory stimul...
N. Jeremy Hill, Thomas Navin Lal, Karin Bierig, Ni...
WACV
2002
IEEE
14 years 23 days ago
A Real-time Precrash Vehicle Detection System
— This paper presents an in-vehicle real-time monocular precrash vehicle detection system. The system acquires grey level images through a forward facing low light camera and ach...
Zehang Sun, Ronald Miller, George Bebis, David DiM...
PAMI
2008
302views more  PAMI 2008»
13 years 7 months ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos
ICASSP
2010
IEEE
13 years 8 months ago
Camera-based clear path detection
In using image analysis to assist a driver to avoid obstacles on the road, traditional approaches rely on various detectors designed to detect different types of objects. We propo...
Qi Wu, Wende Zhang, Tsuhan Chen, B. V. K. Vijaya K...