Understanding evolved genetic programs for a real world object detection problem

Ciesielski, V, Innes, A, John, S and Mamutil, J 2005, 'Understanding evolved genetic programs for a real world object detection problem', in M. Keijzer et al. (ed.) Proceedings of the Eighth European Conference of Genetic Programming 2005, Lausanne, 10 March 2005.


Document type: Conference Paper
Collection: Conference Papers

Title Understanding evolved genetic programs for a real world object detection problem
Author(s) Ciesielski, V
Innes, A
John, S
Mamutil, J
Year 2005
Conference name European Conference of Genetic Programming
Conference location Lausanne
Conference dates 10 March 2005
Proceedings title Proceedings of the Eighth European Conference of Genetic Programming 2005
Editor(s) M. Keijzer et al.
Publisher Springer
Place of publication Heidelberg
Abstract We describe an approach to understanding evolved programs for a real world object detection problem, that of finding orthodontic landmarks in cranio-facial X-Rays. The approach involves modifying the fitness function to encourage the evolution of small programs, limiting the function set to a minimal number of operators and limiting the number of terminals (features). When this was done for two landmarks, an easy one and a difficult one, the evolved programs implemented a linear function of the features. Analysis of these linear functions revealed that underlying regularities were being captured and that successful evolutionary runs usually terminated with the best programs implementing one of a small number of underlying algorithms. Analysis of these algorithms revealed that they are a realistic solution to the object detection problem, given the features and operators available.
Subjects Neural, Evolutionary and Fuzzy Computation
Keyword(s) genetic programs
object detection
DOI - identifier 10.1007/b107383
Copyright notice © Springer-Verlag Berlin Heidelberg 2005
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