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CEC
2010
IEEE
12 years 11 months ago
Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming
Abstract— In this paper, we describe a method for discriminating between thyroid cell lines. Five commercial thyroid cell lines were obtained, ranging from non-cancerous to cance...
Michael A. Lones, Stephen L. Smith, Andrew T. Harr...
ICPR
2008
IEEE
14 years 8 months ago
Evolving boundary detectors for natural images via Genetic Programming
Boundary detection constitutes a crucial step in many computer vision tasks. We present a novel learning approach to automatically construct a boundary detector for natural images...
Ilan Kadar, Moshe Sipper, Ohad Ben-Shahar
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
14 years 1 months ago
Adapting Representation in Genetic Programming
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees....
Cezary Z. Janikow
EUROGP
2005
Springer
115views Optimization» more  EUROGP 2005»
14 years 1 months ago
Genetic Programming in Wireless Sensor Networks
Abstract. Wireless sensor networks (WSNs) are medium scale manifestations of a paintable or amorphous computing paradigm. WSNs are becoming increasingly important as they attain gr...
Derek M. Johnson, Ankur Teredesai, Robert T. Salta...
ICML
1998
IEEE
14 years 8 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi