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ISBI
2004
IEEE
16 years 3 months ago
Incremental Activation Detection in fMRI Series Using Kalman Filtering
We propose a new detection algorithm for functional magnetic resonance imaging (fMRI) data. Our basic idea is to use an extended Kalman filter (EKF) to fit a general linear model ...
Alexis Roche, Jean-Baptiste Poline, Pierre-Jean La...
135
Voted
BMCBI
2007
139views more  BMCBI 2007»
15 years 2 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
246
Voted
ICPR
2002
IEEE
15 years 7 months ago
Combining Kalman Filtering and Mean Shift for Real Time Eye Tracking under Active IR Illumination
Most eye trackers based on active IR illumination require distinctive bright pupil effect to work well. However, due to a variety of factors such as eye closure, eye occlusion, an...
Zhiwei Zhu, Qiang Ji, Kikuo Fujimura, Kuangchih Le...
100
Voted
ICML
2010
IEEE
15 years 3 months ago
Active Learning for Multi-Task Adaptive Filtering
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
Abhay Harpale, Yiming Yang
115
Voted
MICCAI
2009
Springer
16 years 3 months ago
Actin Filament Tracking Based on Particle Filters and Stretching Open Active Contour Models
We introduce a novel algorithm for actin filament tracking and elongation measurement. Particle Filters (PF) and Stretching Open Active Contours (SOAC) work cooperatively to simpli...
Hongsheng Li, Tian Shen, Dimitrios Vavylonis, X...