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» A Markov Random Field Model of Microarray Gridding
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ICC
2007
IEEE
160views Communications» more  ICC 2007»
15 years 4 months ago
Efficient Coverage Planning for Grid-Based Wireless Sensor Networks
- In this paper we study efficient triangular grid-based sensor deployment planning for coverage when sensor placements are perturbed by random errors around their corresponding gr...
Glen Takahara, Kenan Xu, Hossam S. Hassanein
CVPR
2010
IEEE
15 years 3 months ago
Towards Semantic Embedding in Visual Vocabulary
Visual vocabulary serves as a fundamental component in many computer vision tasks, such as object recognition, visual search, and scene modeling. While state-of-the-art approaches...
R.-R. Ji, Hongxun Yao, Xiaoshuai Sun
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 3 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...
ICCV
2009
IEEE
14 years 7 months ago
Analysis of orientation and scale in smoothly varying textures
We present a novel representation for modeling textured regions subject to smooth variations in orientation and scale. Utilizing the steerable pyramid of Simoncelli and Freeman as...
Jason Chang, John W. Fisher III
DAGM
2008
Springer
14 years 11 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr