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PCM
2004
Springer
127views Multimedia» more  PCM 2004»
13 years 10 months ago
Using a Non-prior Training Active Feature Model
This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPTAFM) framework. The proposed algorithm mainly focus...
Sangjin Kim, Jinyoung Kang, Jeongho Shin, Seongwon...
ICASSP
2008
IEEE
13 years 11 months ago
Corrected tandem features for acoustic model training
This paper describes a simple method for significantly improving Tandem features used to train acoustic models for large-vocabulary speech recognition. The linear activations at ...
Arlo Faria, Nelson Morgan
IJCAI
2007
13 years 6 months ago
Common Sense Based Joint Training of Human Activity Recognizers
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however,...
Shiaokai Wang, William Pentney, Ana-Maria Popescu,...
BMCBI
2007
139views more  BMCBI 2007»
13 years 4 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
ECCV
2008
Springer
14 years 6 months ago
Locating Facial Features with an Extended Active Shape Model
We make some simple extensions to the Active Shape Model of Cootes et al. [4], and use it to locate features in frontal views of upright faces. We show on independent test data tha...
Stephen Milborrow, Fred Nicolls