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» Hierarchical Clustering of a Mixture Model
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IDA
1998
Springer
13 years 7 months ago
Self-Organized-Expert Modular Network for Classification of Spatiotemporal Sequences
We investigate a form of modular neural network for classification with (a) pre-separated input vectors entering its specialist (expert) networks, (b) specialist networks which ar...
Sylvian R. Ray, William H. Hsu
ICPR
2010
IEEE
14 years 2 months ago
Pose Estimation of Known Objects by Efficient Silhouette Matching
Pose estimation is essential for automated han- dling of objects. In many computer vision applications only the object silhouettes can be acquired reliably, because untextured or s...
Christian Reinbacher, Matthias Rüther, Horst Bisc...
JMLR
2011
167views more  JMLR 2011»
13 years 2 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
ICMI
2010
Springer
172views Biometrics» more  ICMI 2010»
13 years 5 months ago
Modelling and analyzing multimodal dyadic interactions using social networks
Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore th...
Sergio Escalera, Petia Radeva, Jordi Vitrià...
ECAI
2004
Springer
14 years 1 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana