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» Learning Hierarchical Shape Models from Examples
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ECCV
2010
Springer
14 years 1 months ago
On Parameter Learning in CRF-based Approaches to Object Class Image Segmentation
Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Wit...
ICASSP
2011
IEEE
12 years 11 months ago
MCMC inference of the shape and variability of time-response signals
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...
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...
AAAI
2004
13 years 9 months ago
Learning and Inferring Transportation Routines
This paper introduces a hierarchical Markov model that can learn and infer a user's daily movements through the commue model uses multiple levels of abstraction in order to b...
Lin Liao, Dieter Fox, Henry A. Kautz
UM
2005
Springer
14 years 1 months ago
Using Similarity to Infer Meta-cognitive Behaviors During Analogical Problem Solving
We present a computational framework designed to provide adaptive support aimed at triggering learning from problem-solving activities in the presence of worked-out examples. The k...
Kasia Muldner, Cristina Conati