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ICCV
2001
IEEE
16 years 8 months ago
Image Segmentation by Data Driven Markov Chain Monte Carlo
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Zhuowen Tu, Song Chun Zhu, Heung-Yeung Shum
BMCBI
2004
132views more  BMCBI 2004»
15 years 6 months ago
Two-stage normalization using background intensities in cDNA microarray data
Background: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the me...
Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park
EDBTW
2004
Springer
16 years 2 days ago
Clustering Structured Web Sources: A Schema-Based, Model-Differentiation Approach
Abstract. The Web has been rapidly “deepened” with the prevalence of databases online. On this “deep Web,” numerous sources are structured, providing schema-rich data– Th...
Bin He, Tao Tao, Kevin Chen-Chuan Chang
PODS
2009
ACM
119views Database» more  PODS 2009»
16 years 7 months ago
Exceeding expectations and clustering uncertain data
Database technology is playing an increasingly important role in understanding and solving large-scale and complex scientific and societal problems and phenomena, for instance, un...
Sudipto Guha, Kamesh Munagala
WSC
2001
15 years 8 months ago
Quantifying simulation output variability using confidence intervals and statistical process control
Two types of variability can occur in model output: variability between replications and variability within each replication. The objective of the model combined with the type of ...
Amy Jo Naylor