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» Learning spatial concepts from RatSLAM representations
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IVC
2008
182views more  IVC 2008»
14 years 9 months ago
Ontology based complex object recognition
This paper presents an object categorization method. Our approach involves the following aspects of cognitive vision : machine learning and knowledge representation. A major eleme...
Nicolas Maillot, Monique Thonnat
ATAL
2006
Springer
15 years 1 months ago
Ontology-guided learning to improve communication between groups of agents
We present a general method for agents using ontologies as part of their knowledge representation to teach each other concepts to improve their communication and thus cooperation ...
Mohsen Afsharchi, Behrouz H. Far, Jörg Denzin...
IJCAI
1997
14 years 10 months ago
Using Case-Based Reasoning in Interpreting Unsupervised Inductive Learning Results
The objective of this work is to interpret inductive results obtained by the unsupervised learning method OSHAM. We briefly introduce the learning process of OSHAM, that extracts ...
Tu Bao Ho, Chi Main Luong
RSS
2007
129views Robotics» more  RSS 2007»
14 years 11 months ago
Spatially-Adaptive Learning Rates for Online Incremental SLAM
— Several recent algorithms have formulated the SLAM problem in terms of non-linear pose graph optimization. These algorithms are attractive because they offer lower computationa...
Edwin Olson, John J. Leonard, Seth J. Teller
DAGM
1997
Springer
15 years 1 months ago
A Feature Map Approach to Real-Time 3-D Object Pose Estimation from Single 2-D Perspective Views
A novel approach to the computation of an approximate estimate of spatial object pose from camera images is proposed. The method is based on a neural network that generates pose hy...
S. Winkler, Patrick Wunsch, Gerd Hirzinger