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MR image classification by the neural network and the genetic algorithms

机译:先生通过神经网络和遗传算法进行图像分类

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A novel neural network trained by the genetic algorithms (GAs) is presented. Each neuron of the network forms a closed region in an input space. The locations of the centers of the closed regions (CR) are optimized in order to minimize the number of the neurons used and to improve the classification performance. After the network is trained by the set which is formed by the supervisor, it is used to classify a magnetic resonance (MR) image with a tumor.
机译:提出了由遗传算法(气体)训练的新型神经网络。网络的每个神经元在输入空间中形成闭合区域。优化封闭区域(Cr)的中心的位置,以最小化所用神经元的数量并提高分类性能。在网络由由主管形成的集合训练之后,它用于将磁共振(MR)图像与肿瘤分类。

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