An unsupervised segmentation of SAR imagery based on Multiscale image block is proposed.
提出了一种基于多尺度图像块的SAR图像无监督分割方法。
The paper presents an unsupervised segmentation model based on multiple level sets evolution for high resolution satellite imagery.
提出多水平集演化的非监督高分辨率影像分割模型，避免传统多水平集方法中的区域重叠问题。
The traditional watershed segmentation algorithm is a kind of unsupervised segmentation algorithms, which produces sub-regions without semantic representation.
传统的分水岭分割算法属于无监督的图像分割算法，分割获得的子区域往往不具备现实的语义信息。
In order to overcome the weakness of statistical texture segmentation method, a new unsupervised texture segment algorithm, based on multi-resolution statistical model, was present.
针对基于统计的纹理分割算法存在的不足，提出了一种新的多分辨模型下的无监督统计纹理分割算法。
Three images results of segmentation are presented and demonstrate the efficiency of QPSO algorithms to automatic and unsupervised texture segmentation.
给出了三幅图像的分割效果，证明了QPSO算法在自动的和无监督的纹理分割上具有很好的效果。
This paper proposes a new neural network model UMAN to perform unsupervised image segmentation.
本文提出了一种新的神经网络模型UMAN，以实现非监督的图象分割。
This paper presents a novel unsupervised image segmentation algorithm based on hidden Markov random field(HMRF) model.
研究了基于隐马尔可夫随机场（HMRF）模型的无监督图像分割问题。
A number of supervised and unsupervised pattern recognition techniques have been proposed in recent years for the tissue segmentation and quantitative analysis of magnetic resonance images.
近年来提出了许多监督和非监督模式识别技术用于磁共振图象的组织分类和定量分析。
This paper proposes an algorithm based on curve evolution for unsupervised texture segmentation.
提出了一种基于曲线演化的非监督式纹理分割算法。
Furthermore, in order to solve the model selection problems of unsupervised image segmentation, the sum of squared error criterion with penalty term is proposed.
而且，针对无监督图像分割的模型选择问题提出了带惩罚项的误差平方和阶次判定准则。
This kind of unsupervised clustering method can search for the optimal number of output nodes automatically to get the number of textures in the 'image, and finish the automatic segmentation.
这种无监督的聚类方法能够自动搜索最佳的网络输出节点数而获取图像中的目标数，从而完成对图像的自动分割。
It is a procedure of the label following an unsupervised fuzzy clustering that fuzzy c-means (FCM) algorithm is applied to image segmentation.
算法用于图像分割是一种非监督模糊聚类后再标定的过程。
This paper presents a novel approach to unsupervised texture segmentation according to a very general nonparametric statistical model of image neighborhoods.
针对基于统计的纹理分割算法存在的不足，提出了一种新的多分辨模型下的无监督统计纹理分割算法。
In this paper, an unsupervised online temporal segmentation algorithm is presented, and then the segmentation result is recognized by HMM.
提出了一种无监督的行为序列分割算法，并对分割结果进行识别。
In this paper, an unsupervised online temporal segmentation algorithm is presented, and then the segmentation result is recognized by HMM.
提出了一种无监督的行为序列分割算法，并对分割结果进行识别。
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