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» Two-Dimensional Active Learning for image classification
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IPMI
2011
Springer
12 years 9 months ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
CVPR
2004
IEEE
14 years 8 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
IJCAI
2007
13 years 7 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
AAAI
2010
13 years 7 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
IVC
2006
154views more  IVC 2006»
13 years 6 months ago
Manifold based analysis of facial expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embed...
Ya Chang, Changbo Hu, Rogerio Feris, Matthew Turk