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TNN
2008
106views more  TNN 2008»
15 years 6 months ago
Unsupervised Segmentation With Dynamical Units
In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
INTERSPEECH
2010
15 years 1 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
SIAMREV
2011
63views more  SIAMREV 2011»
14 years 9 months ago
Discrete Symbol Calculus
This paper deals with efficient numerical representation and manipulation of differential and integral operators as symbols in phase-space, i.e., functions of space x and frequen...
Laurent Demanet, Lexing Ying
CVPR
2012
IEEE
13 years 9 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis
ICIP
2009
IEEE
16 years 7 months ago
A Resource Allocation Framework For Summarizing Team Sport Videos
We propose a flexible summarization framework for teamsport videos, which is able to integrate both the knowledge about displayed content (e.g. level of interest, type of view, et...