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» On Weak Markov's Principle
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CVPR
2007
IEEE
14 years 9 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
DAC
1999
ACM
14 years 8 months ago
Hypergraph Partitioning for VLSI CAD: Methodology for Heuristic Development, Experimentation and Reporting
We illustrate how technical contributions in the VLSI CAD partitioning literature can fail to provide one or more of: (i) reproducible results and descriptions, (ii) an enabling a...
Andrew E. Caldwell, Andrew B. Kahng, Andrew A. Ken...
MICCAI
2007
Springer
14 years 8 months ago
Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy
In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of "sharpness" and the joint registration-segmentation o...
B. T. Thomas Yeo, Mert R. Sabuncu, Rahul Desikan, ...
ICML
1998
IEEE
14 years 8 months ago
Heading in the Right Direction
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
Hagit Shatkay, Leslie Pack Kaelbling
IROS
2007
IEEE
162views Robotics» more  IROS 2007»
14 years 1 months ago
Genetic MRF model optimization for real-time victim detection in search and rescue
— One primary goal in rescue robotics is to deploy a team of robots for coordinated victim search after a disaster. This requires robots to perform subtasks, such as victim detec...
Alexander Kleiner, Rainer Kümmerle