Optimization of Image Processing by Genetic and Evolutionary Computation: How to Realize Still Better Performance.
作者： Hisashi Shimodaira
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摘要: In this paper, we examine the results of major previous attempts to apply genetic and evolutionary computation (GEC) image processing. many problems, accuracy (quality) solutions obtained by GEC-based methods is better than that other such as conventional methods, neural networks simulated annealing. However, time required satisfactory in some whereas it unsatisfactory problems. We consider current problems present following measures achieve still performance: (1) utilizing competent GECs, (2) incorporating search algorithms local hill climbing algorithms, (3) hybridizing with processing (4) modeling given problem smaller parameters possible, (5) using parallel processors evaluate fitness function.
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