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» Clustering Moving Objects via Medoid Clusterings
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KDD
2010
ACM
208views Data Mining» more  KDD 2010»
13 years 6 months ago
Towards mobility-based clustering
Identifying hot spots of moving vehicles in an urban area is essential to many smart city applications. The practical research on hot spots in smart city presents many unique feat...
Siyuan Liu, Yunhuai Liu, Lionel M. Ni, Jianping Fa...
ICMCS
2009
IEEE
219views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Moving targets labeling and correspondence over multi-camera surveillance system based on Markov network
In this paper, we propose an efficient way to simultaneously label and map targets over a multi-camera surveillance system. In the system, we first fuse the detection results from...
Chingchun Huang, Sheng-Jyh Wang
ICASSP
2011
IEEE
12 years 11 months ago
Detection of upper airway narrowing via classification of LPC coefficients: Implications for obstructive sleep apnea diagnosis
The similarities between unvoiced speech sounds and turbulent breath sounds were used to detect change in sound characteristics caused by narrowing of the upper airway (UA), simil...
Hisham Alshaer, Martha Garcia, M. Hossein Radfar, ...
ICDM
2005
IEEE
146views Data Mining» more  ICDM 2005»
14 years 1 months ago
Merging Interface Schemas on the Deep Web via Clustering Aggregation
We consider the problem of integrating a large number of interface schemas over the Deep Web, The scale of the problem and the diversity of the sources present serious challenges ...
Wensheng Wu, AnHai Doan, Clement T. Yu
PDPTA
2003
13 years 9 months ago
Managing Flocking Objects with an Octree Spanning a Parallel Message-Passing Computer Cluster
We investigate the management of flocking mobile objects using a parallel message-passing computer cluster. An octree, a data structure well-known for use in managing a 3D space, ...
Thomas E. Portegys, Kevin M. Greenan