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» Using Maximum Entropy for Automatic Image Annotation
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ICCV
2007
IEEE
14 years 2 months ago
Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
ICCV
2001
IEEE
14 years 9 months ago
Segmentation of the Left Ventricle in Cardiac MR Images
This paper describes a segmentation technique to automatically extract the myocardium in 4 0 cardiac M R images for quantitative cardiac analysis and the diagnosis of patients. Th...
Marie-Pierre Jolly, Nicolae Duta, Gareth Funka-Lea
ICCV
2009
IEEE
15 years 27 days ago
Learning Actions From the Web
This paper proposes a generic method for action recognition in uncontrolled videos. The idea is to use images collected from the Web to learn representations of actions and use ...
Nazli Ikizler-Cinbis, R. Gokberk Cinbis, Stan Scla...
LREC
2010
152views Education» more  LREC 2010»
13 years 9 months ago
A Software Toolkit for Viewing Annotated Multimodal Data Interactively over the Web
This paper describes a software toolkit for the interactive display and analysis of automatically extracted or manually derived annotation features of visual and audio data. It ha...
Nick Campbell, Akiko Tabata
ICML
2006
IEEE
14 years 8 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...