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AMAI
2004
Springer
14 years 27 days ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
GPEM
2008
98views more  GPEM 2008»
13 years 7 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg
CVPR
2009
IEEE
15 years 2 months ago
Material Classification using BRDF Slices
Segmenting images into distinct material types is a very useful capability. Most work in image segmentation addresses the case where only a single image is available. Some methods ...
Oliver Wang (University of California, Santa Cruz)...
ECCV
2006
Springer
14 years 9 months ago
Learning and Incorporating Top-Down Cues in Image Segmentation
Abstract. Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, rec...
Xuming He, Richard S. Zemel, Debajyoti Ray
ICTAI
2007
IEEE
14 years 1 months ago
Photometric Invariant Projective Registration Using ECC Maximization
The ability of an algorithm to accurately estimate the parameters of the geometric transformation which aligns two image profiles even in the presence of photometric distortions ...
Georgios D. Evangelidis, Emmanouil Z. Psarakis