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GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
13 years 10 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
TMI
2002
155views more  TMI 2002»
13 years 5 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...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 1 months ago
Model-on-Demand predictive control for nonlinear hybrid systems with application to adaptive behavioral interventions
This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem b...
Naresh N. Nandola, Daniel E. Rivera
TIP
2010
155views more  TIP 2010»
13 years 4 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
CORR
2007
Springer
99views Education» more  CORR 2007»
13 years 6 months ago
Fast Selection of Spectral Variables with B-Spline Compression
The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables ...
Fabrice Rossi, Damien François, Vincent Wer...