文件名称:ELM--of-image-segmentation
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以极限学习机的图
像分割算法为基础， 在确定了最优参数的基础上， 建立了基于ELM的图像分割算法， 并且通过仿真实验对算法的正确性和
有效性进行了验证， 指出这种算法能够更加快速地完成对图像的分割， 并且图像分割孤立点少， 边缘明显， 同时该算法大
大地缩短了样本的训练时间。-In image segmentation algorithm based on machine learning limit, in determining the optimum parameters based on established ELM-based image segmentation algorithm, and the simulation results of the correctness and effectiveness of the algorithm was validated, noting that the algorithm to more quickly complete the image segmentation, image segmentation and isolated points less obvious edge, while the algorithm greatly shorten the training time samples.
像分割算法为基础， 在确定了最优参数的基础上， 建立了基于ELM的图像分割算法， 并且通过仿真实验对算法的正确性和
有效性进行了验证， 指出这种算法能够更加快速地完成对图像的分割， 并且图像分割孤立点少， 边缘明显， 同时该算法大
大地缩短了样本的训练时间。-In image segmentation algorithm based on machine learning limit, in determining the optimum parameters based on established ELM-based image segmentation algorithm, and the simulation results of the correctness and effectiveness of the algorithm was validated, noting that the algorithm to more quickly complete the image segmentation, image segmentation and isolated points less obvious edge, while the algorithm greatly shorten the training time samples.
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极限学习机在图像分割中的应用.pdf