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» Learning Object Representations Using Sequential Patterns
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GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
14 years 9 days ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
RSS
2007
145views Robotics» more  RSS 2007»
13 years 9 months ago
Semantic Modeling of Places using Objects
— While robot mapping has seen massive strides , higher level abstractions in map representation are still not widespread. Maps containing semantic concepts such as objects and l...
Ananth Ranganathan, Frank Dellaert
ICIP
2007
IEEE
14 years 9 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson
AIPS
2007
13 years 10 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
ICALT
2010
IEEE
13 years 8 months ago
Spatializing Social Practices in Mobile Game-Based Learning
The objectives of this paper are to explore the characteristics of patterns of participation in social and gameplay spaces outside the classroom of 10 fifteen-year-olds engaging in...
Susan Gwee, Yam-San Chee, Ek-Ming Tan