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Research on Genetic Segmentation and Recognition Algorithms

机译:遗传分割与识别算法研究

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Proposed an improved genetic segmentation algorithm and recognition method base on PSO. In the genetic algorithm, 2-dimention chromosome coding is adopted; initialization of population with stochastic and symmetrical methods is produced to keep the variety of the population; OTSU is adopted to be as fitness function; a new individual is introduced in updated population. Abstracted three main components from the segmented image, and used neural networks trained by PSO to recognize the blood cells types. Experiments show that good results can be achieved steadily and quickly.
机译:提出了一种改进的基于粒子群算法的遗传分割算法和识别方法。在遗传算法中,采用了二维染色体编码。用随机和对称方法初始化种群,以保持种群的多样性;采用OTSU作为适应度函数;在更新的人口中引入了新的个体。从分割的图像中提取了三个主要成分,并使用了由PSO训练的神经网络来识别血细胞类型。实验表明,可以稳定,快速地取得良好的效果。

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