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TMI
1998
155views more  TMI 1998»
13 years 7 months ago
Spatio-temporal fMRI Analysis using Markov Random Fields
Abstract—Functional magnetic resonance images (fMRI’s) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activa...
Xavier Descombes, Frithjof Kruggel, D. Yves von Cr...
VLSISP
2002
114views more  VLSISP 2002»
13 years 7 months ago
Image processing using cellular neural networks based on multi-valued and universal binary neurons
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an a...
Igor N. Aizenberg, Constantine Butakoff
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 6 months ago
The LASSO risk for gaussian matrices
We consider the problem of learning a coefficient vector x0 ∈ RN from noisy linear observation y = Ax0 + w ∈ Rn . In many contexts (ranging from model selection to image proce...
Mohsen Bayati, Andrea Montanari
JUCS
2010
134views more  JUCS 2010»
13 years 6 months ago
Track-To-Track Measurement Fusion Architectures and Correlation Analysis
: The purpose of this paper is to address some theoretical issues related to the track-to-track fusion problem when the measurements tracking the same target are inherently correla...
Mourad Oussalah, Zahir Messaoudi, Abdelaziz Ouldal...
PAMI
2010
396views more  PAMI 2010»
13 years 6 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu