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» Algorithms for Spatial Outlier Detection
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KDD
2002
ACM
113views Data Mining» more  KDD 2002»
14 years 8 months ago
Scalable robust covariance and correlation estimates for data mining
Covariance and correlation estimates have important applications in data mining. In the presence of outliers, classical estimates of covariance and correlation matrices are not re...
Fatemah A. Alqallaf, Kjell P. Konis, R. Douglas Ma...
MOBISYS
2007
ACM
14 years 7 months ago
Algorithm to automatically detect abnormally long periods of inactivity in a home
An algorithm has been developed to automatically construct individual models of normal activity within a home using motion sensor data. Alerts can be generated when a period of in...
Paul Cuddihy, Jenny Weisenberg, Catherine Graichen...
ICDM
2009
IEEE
153views Data Mining» more  ICDM 2009»
13 years 5 months ago
A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters
Clustering methods usually require to know the best number of clusters, or another parameter, e.g. a threshold, which is not ever easy to provide. This paper proposes a new graph-b...
Fabrice Muhlenbach, Stéphane Lallich
BMCBI
2006
130views more  BMCBI 2006»
13 years 7 months ago
Spatial normalization of array-CGH data
Background: Array-based comparative genomic hybridization (array-CGH) is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, no...
Pierre Neuvial, Philippe Hupé, Isabel Brito...
ECCV
2008
Springer
14 years 9 months ago
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo
We propose an algorithm to improve the quality of depth-maps used for Multi-View Stereo (MVS). Many existing MVS techniques make use of a two stage approach which estimates depth-m...
Carlos Hernández, George Vogiatzis, Neill D...