In this paper, an environment for using genetic programming is presented. Although not restricted to a specific domain, our intention is to apply it to image processing problems such as fingerprint recognition. The environment performs tasks like: population management, genetic operators and distributed parallel evaluation of the programs. Furthermore, it provides a framework for implementation of the problemspecific part. Using object-oriented methods, the environment is designed to offer a high degree of flexibility and ease of use. The GP environment uses distributed fitness evaluation, which can be used on existing computer networks. The system is optimized for efficiency of distribution. Experiments are included in the paper to illustr...
Abstract—In this article, we evaluate the applicability of Genetic Programming (GP) for the evolutio...
Combining domain knowledge about both imaging processing and machine learning techniques can expand ...
A parallel implementation of Genetic Programming using PVM is described. Two different topologies fo...
In this paper, an environment for using genetic programming is presented. Although not restricted to...
This paper presents a distributed approach to parallelise Genetic Programming on the Internet. The m...
A distributed approach for parallelising Genetic Programming (GP) on the Internet is proposed and it...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
We proposed a distributed approach for parallelising Genetic Programming on the Internet. The approa...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
In this paper we present an approach to the interactive development of programs for image enhancemen...
This paper describes an approach to using GP for image analysis based on the idea that image enhance...
Genetic Programming (GP) is an automatic programming methodology using mechanisms inspired by biolo...
Some recent work in the field of Genetic Programming (GP) has been concerned with finding optimum re...
Abstract—In this article, we evaluate the applicability of Genetic Programming (GP) for the evolutio...
Combining domain knowledge about both imaging processing and machine learning techniques can expand ...
A parallel implementation of Genetic Programming using PVM is described. Two different topologies fo...
In this paper, an environment for using genetic programming is presented. Although not restricted to...
This paper presents a distributed approach to parallelise Genetic Programming on the Internet. The m...
A distributed approach for parallelising Genetic Programming (GP) on the Internet is proposed and it...
Genetic programming (GP) is a machine learning technique that is based on the evolution of computer ...
We proposed a distributed approach for parallelising Genetic Programming on the Internet. The approa...
Parallel genetic algorithms are usually implemented on parallel machines or distributed systems. Thi...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
Genetic programming is an automatic programming method that creates computer programs to satisfy a s...
In this paper we present an approach to the interactive development of programs for image enhancemen...
This paper describes an approach to using GP for image analysis based on the idea that image enhance...
Genetic Programming (GP) is an automatic programming methodology using mechanisms inspired by biolo...
Some recent work in the field of Genetic Programming (GP) has been concerned with finding optimum re...
Abstract—In this article, we evaluate the applicability of Genetic Programming (GP) for the evolutio...
Combining domain knowledge about both imaging processing and machine learning techniques can expand ...
A parallel implementation of Genetic Programming using PVM is described. Two different topologies fo...