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EMMCVPR
2005
Springer
15 years 11 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert
VLSM
2005
Springer
15 years 11 months ago
Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
Mariano Rivera, Omar Ocegueda, José L. Marr...
EH
2003
IEEE
136views Hardware» more  EH 2003»
15 years 11 months ago
Experimental Results in Evolutionary Fault-Recovery for Field Programmable
This paper presents experimental results of fast intrinsic evolutionary design and evolutionary fault recovery of a 4-bit Digital to Analog Converter (DAC) using the JPL stand-alo...
Ricardo Salem Zebulum, Didier Keymeulen, Vu Duong,...
ICPR
2000
IEEE
15 years 10 months ago
Nonparametric Markov Random Field Model Analysis of the MeasTex Test Suite
This paper looks at the nonparametric, multiscale, Markov Random Field (MRF) model and its application in classifying the MeasTex Test Suite. The MeasTex Test Suite is a standard ...
Rupert Paget, I. Dennis Longstaff
VISUALIZATION
1999
IEEE
15 years 10 months ago
Tensorlines: Advection-Diffusion Based Propagation through Diffusion Tensor Fields
Tracking linear features through tensor field datasets is an open research problem with widespread utility in medical and engineering disciplines. Existing tracking methods, which...
David M. Weinstein, Gordon L. Kindlmann, Eric C. L...