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» Querying Probabilistic Information Extraction
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HRI
2010
ACM
15 years 11 months ago
Toward understanding natural language directions
—Speaking using unconstrained natural language is an intuitive and flexible way for humans to interact with robots. Understanding this kind of linguistic input is challenging be...
Thomas Kollar, Stefanie Tellex, Deb Roy, Nicholas ...
DILS
2006
Springer
15 years 7 months ago
Link Discovery in Graphs Derived from Biological Databases
Public biological databases contain vast amounts of rich data that can also be used to create and evaluate new biological hypothesis. We propose a method for link discovery in biol...
Petteri Sevon, Lauri Eronen, Petteri Hintsanen, Ki...
NIPS
2007
15 years 5 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
NIPS
2004
15 years 5 months ago
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Le Lu, Gregory D. Hager, Laurent Younes
134
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DAGM
2010
Springer
15 years 2 months ago
3D Reconstruction Using an n-Layer Heightmap
We present a novel method for 3D reconstruction of urban scenes extending a recently introduced heightmap model. Our model has several advantages for 3D modeling of urban scenes: i...
David Gallup, Marc Pollefeys, Jan-Michael Frahm