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» Crime Pattern Detection Using Data Mining
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129
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ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
15 years 9 days ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
124
Voted
BMCBI
2010
147views more  BMCBI 2010»
15 years 2 months ago
baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data
Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Thomas J. Hardcastle, Krystyna A. Kelly
192
Voted
CVPR
2012
IEEE
13 years 5 months ago
Tracking many vehicles in wide area aerial surveillance
Wide area aerial surveillance data has recently proliferated and increased the demand for multi-object tracking algorithms. However, the limited appearance information on every ta...
Jan Prokaj, Xuemei Zhao, Gérard G. Medioni
104
Voted
PREMI
2005
Springer
15 years 8 months ago
Pattern Recognition in Video
Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon...
Rama Chellappa, Ashok Veeraraghavan, Gaurav Aggarw...
135
Voted
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
15 years 6 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar