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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
CANDC
2007
ACM
13 years 8 months ago
Dynamical characteristics of bacteria clustering by self-generated attractants
Motivated by the recent work on Escherichia coli bacteria clustering [Park, S., Wolanin, P.M., Yuzbashyan, E.A., Lin, H., Darnton, N.C., Stock, J.B., Silberzan, P., Austin, R., 20...
MunJu Kim, Songjoon Baek, Sung Hoon Jung, Kwang-Hy...
AVBPA
2003
Springer
101views Biometrics» more  AVBPA 2003»
14 years 3 days ago
Gait Shape Estimation for Identification
A method is presented for identifying individuals by shape, given a sequence of noisy silhouettes segmented from video. A spectral partitioning framework is used to cluster similar...
David Tolliver, Robert T. Collins
TCS
2010
13 years 6 months ago
Iterative compression and exact algorithms
Iterative Compression has recently led to a number of breakthroughs in parameterized complexity. Here, we show that the technique can also be useful in the design of exact exponen...
Fedor V. Fomin, Serge Gaspers, Dieter Kratsch, Mat...
ACL
2010
13 years 6 months ago
Improved Unsupervised POS Induction through Prototype Discovery
We present a novel fully unsupervised algorithm for POS induction from plain text, motivated by the cognitive notion of prototypes. The algorithm first identifies landmark cluster...
Omri Abend, Roi Reichart, Ari Rappoport