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Em segmentation algorithm applied for image segmentation
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从ML-EM 重建算法入手，分析了贝叶斯模型的一些关键点，针对采用传统方法求解MAP问题的局限性，提出一种用于正电子成像的贝叶斯神经网络重建算法，为了保留边缘信息，引入了二进制的保边缘变量，并应用共轭神经网络求解，模拟的重建结果表明，应用这种算法可以得到比ML-EM 算法更好的重建图像@-From the ML-EM reconstruction algorithm start with an analysis of Bayesian model some of the key points,
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EM algorithm mean shift algorithm for image segmentation, at the same time have demo program with the ultimate view of segmentation results
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基于高斯混合模型，经由一种高效率的EM-MAP算法，解决图像超分辨率重建问题-A general framework for solving image inverse problems is introduced in this paper. The approach is
based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm.
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EM算法正确收敛性的探讨，用于在图像处理中图像分割时应用EM，而算法有时不收敛的情况。-The EM Algorithm Convergence of the correct application of the EM for image processing in image segmentation algorithm sometimes does not converge.
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em algorithm for image denoising
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