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ICPR
2006
IEEE
14 years 5 months ago
Active Feature Models
In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are ...
Georg Langs, Philipp Peloschek, Rene Donner, Micha...
ICCV
2003
IEEE
14 years 6 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan
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...
TMI
2002
155views more  TMI 2002»
13 years 4 months ago
Active Shape Model Segmentation with Optimal Features
Abstract--An active shape model segmentation scheme is presented that is steered by optimal local features, contrary to normalized first order derivative profiles, as in the origin...
Bram van Ginneken, Alejandro F. Frangi, Joes Staal...
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