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CIARP
2007
Springer
14 years 2 months ago
Learning in Computer Vision: Some Thoughts
Abstract. It is argued that the ability to generalise is the most important characteristic of learning and that generalisation may be achieved only if pattern recognition systems l...
Maria Petrou
IROS
2006
IEEE
107views Robotics» more  IROS 2006»
14 years 2 months ago
Heterogeneous and Hierarchical Cooperative Learning via Combining Decision Trees
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...
COGSR
2011
105views more  COGSR 2011»
13 years 3 months ago
Inductive rule learning on the knowledge level
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
Ute Schmid, Emanuel Kitzelmann
ICCV
2005
IEEE
14 years 2 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
CVPR
2004
IEEE
14 years 10 months ago
Object-Based Image Retrieval Using the Statistical Structure of Images
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...