So far, some studies of image characteristics and inference have been done. However, thoes methods obtain results convergently, not divergently. In this study we develop a system in which results are obtained divergently using 3 genetics algorithm that bases on the the theory of a life's evolution (selection and mutation), and compare these results with those obtained by a neural network using some sample concepts. Subsequently, we confirm the viability of the system using the genetics algorithm. Further, we develop a system connecting genetics algorithm and neural network in paralle, and as a result we confirm that this system gets results has advantages of both of methods, and can controls these advantages by a parameter.
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