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» Learning a Generative Model for Structural Representations
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AMKM
2003
Springer
15 years 7 months ago
Discovering, Visualizing, and Sharing Knowledge through Personalized Learning Knowledge Maps
This paper presents an agent-based approach to semantic exploration and knowledge discovery in large information spaces by means of capturing, visualizing and making usable implic...
Jasminko Novak, Michael Wurst, Monika Fleischmann,...
114
Voted
COLING
2002
15 years 2 months ago
Hierarchical Orderings of Textual Units
Text representation is a central task for any approach to automatic learning from texts. It requires a format which allows to interrelate texts even if they do not share content w...
Alexander Mehler
IROS
2009
IEEE
145views Robotics» more  IROS 2009»
15 years 9 months ago
Utilizing prior information to enhance self-supervised aerial image analysis for extracting parking lot structures
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
Young-Woo Seo, Chris Urmson
CVPR
2007
IEEE
16 years 4 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
145
Voted
ECCV
2006
Springer
16 years 4 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann