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KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 9 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
ICIAP
2001
Springer
14 years 9 months ago
Recognition of Shape-Changing Hand Gestures Based on Switching Linear Model
We present a method to track and recognize shape-changing hand gestures simultaneously. The switching linear model using active contour model well corresponds to temporal shapes a...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...
ICDCS
2009
IEEE
14 years 6 months ago
CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
Anna Förster, Amy L. Murphy
CVPR
2010
IEEE
14 years 5 months ago
Automatic Discovery of Meaningful Object Parts with Latent CRFs
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a...
Paul Schnitzspan, Stefan Roth, Bernt Schiele
TEI
2010
ACM
197views Hardware» more  TEI 2010»
14 years 3 months ago
Constructing with movement: kinematics
This paper describes Kinematics: a novel construction toy for children consisting of both active (shape-changing or rotating) and passive building blocks. In comparison to similar...
Leonhard Oschuetz, Daniel Wessolek, Wolfgang Sattl...