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» Learning about and through Empirical Modelling
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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...
CVPR
2009
IEEE
15 years 3 months ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...
ECAL
1995
Springer
14 years 2 days ago
Can Development Be Designed? What we May Learn from the Cog Project
Neither `design' nor `evolutionary' approaches to building behavior-based robots feature a role for development in the genesis of behavioral organization. However, the n...
Julie C. Rutkowska
KDD
2009
ACM
262views Data Mining» more  KDD 2009»
14 years 9 months ago
Sentiment analysis of blogs by combining lexical knowledge with text classification
The explosion of user-generated content on the Web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the disc...
Prem Melville, Wojciech Gryc, Richard D. Lawrence
COLING
2008
13 years 10 months ago
Linguistically Annotated BTG for Statistical Machine Translation
Bracketing Transduction Grammar (BTG) is a natural choice for effective integration of desired linguistic knowledge into statistical machine translation (SMT). In this paper, we p...
Deyi Xiong, Min Zhang, AiTi Aw, Haizhou Li