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» Learning a Generative Model for Structural Representations
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CVPR
2009
IEEE
15 years 3 months ago
D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes
Autonomous systems which learn and utilize a limited visual vocabulary have wide spread applications. Enabling such systems to segment a set of cluttered scenes into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...
WSC
2007
13 years 11 months ago
A hybrid epidemic model: combining the advantages of agent-based and equation-based approaches
Agent-based models (ABMs) are powerful in describing structured epidemiological processes involving human behavior and local interaction. The joint behavior of the agents can be v...
Georgiy V. Bobashev, D. Michael Goedecke, Feng Yu,...
ICML
2008
IEEE
14 years 9 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
TCBB
2011
13 years 3 months ago
Learning Genetic Regulatory Network Connectivity from Time Series Data
Recent experimental advances facilitate the collection of time series data that indicate which genes in a cell are expressed. This paper proposes an efficient method to generate th...
Nathan A. Barker, Chris J. Myers, Hiroyuki Kuwahar...
AR
2007
204views more  AR 2007»
13 years 9 months ago
Action recognition and understanding through motor primitives
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...