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» Ontology based complex object recognition
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ACIVS
2006
Springer
14 years 1 months ago
Context-Based Scene Recognition Using Bayesian Networks with Scale-Invariant Feature Transform
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons, we need a novel method that has robustness to the...
Seung-Bin Im, Sung-Bae Cho
AAAI
1993
13 years 11 months ago
Learning Object Models from Appearance
We address the problem of automatically learning object models for recognition and pose estimation. In contrast to the traditional approach, we formulate the recognition problem a...
Hiroshi Murase, Shree K. Nayar
RSCTC
2000
Springer
197views Fuzzy Logic» more  RSCTC 2000»
14 years 1 months ago
Rough Set Approach to CBR
We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
Jan Wierzbicki
ARTMED
2006
75views more  ARTMED 2006»
13 years 10 months ago
Semi-automatic learning of simple diagnostic scores utilizing complexity measures
Objective: Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semiautoma...
Martin Atzmüller, Joachim Baumeister, Frank P...
PAMI
2011
13 years 20 days ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori