Claudette Owens

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According to the Department of Defense, over 10 million acres of land in the US need to be cleared of buried unexploded ordnance (UXO). Worldwide, UXO injures thousands each year. Cleanup costs are prohibitively expensive due to the difficulties in discriminating buried UXO from other inert non-UXO objects. Government agencies are actively searching for(More)
A form of Evolutionary Computation (EC) called Genetic Programming (GP) was used to automatically discover sequences of image noise filters to remove two types of image noise and a type of communications noise associated with a remotely sensed imagery. Sensor noise was modeled by the addition of salt-and-pepper and grayscale noise to the image.(More)
Evolutionary computation (EC) is a general term applied to a group of global optimization techniques whose main characteristics are inspired by biological evolution. Instead of working with one possible solution at a time, they usually start with a population of random solutions. The initial population evolves into a better set of solutions through three(More)
The 2002 CEC paper entitled "Genetic Programming with Smooth Operators for Arithmetic Expressions: Diviplication and Subdition" by Ursem and Krink proposed to blend certain arithmetic operators by interpolation to smooth the transition from one operator to another in the fitness landscape. Inspired by their idea, herein it is shown how to generalize further(More)
Many GECCO papers discuss lessons learned in a particular application, but few papers discuss lessons learned over an ensemble of problem areas. A scan of the tables of contents of the Proceedings from GECCO 2005 and 2006 showed no paper title stressing lessons learned although the term "pitfall" appeared occasionally in abstracts, typically applying to a(More)
How does one choose an initial set of parameters for an evolutionary computing algorithm? Clearly some choices are dictated by the problem itself, such as the encoding of a problem solution, or how much time is available for running the evolution. Others, however, are frequently found by trial-and-error. These may include population sizes, number of(More)
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