An improved FCM algorithm is proposed based on the improvement of hybrid color space.
提出一种基于混合颜色空间的改进的FCM算法。
The result shows that the new algorithm is superior to the traditional FCM algorithm.
实验结果表明，新方法明显优于传统FCM算法。
This method enormously accelerates the FCM algorithm while maintaining the clustering …
该方法使FCM算法运算速度大大提高，且不影响算法的聚类效果。
So standard FCM algorithm was modified and applied to separate the tongue body and tongue coating.
在此基础上，对于标准模糊聚类算法进行了改进并应用于舌象的舌质舌苔分离。
The FCNN is fuzzed by FCM algorithm and improved LMS algorithm is applied to tune the weight of FCNN.
采用模糊C—均值聚类算法对网络进行模糊化，利用改进的LMS算法对网络进行训练。
Finally we combined FCM algorithm with neural network and used them in the design of vehicle classification.
最后，将原fCM算法和神经网络算法相结合，并用于车型的分类设计中。
To overcome the above problem, a novel modified FCM algorithm for image segmentation is presented in this paper.
为了克服上述问题，提出了一种新的基于改进的FCM图像分割算法。
The standard FCM algorithm is not only extremely time-consuming for clustering large data set, but also more sensitive to noise.
标准的FCM算法对大数据样本集进行聚类时极为耗时，而且对噪声比较敏感。
The algorithm is initialized by a statistical histogram based on FCM algorithm, which can speed up the convergence of the algorithm.
算法中使用基于统计直方图的快速FCM算法进行初始化，收敛速度大大提高。
The improved FCM algorithm was adopted to segment images, and automatic fuzzy redistribution algorithm to define the subject degree.
采用改进的FCM算法分割图像，用自动模糊重分布的算法确定隶属度。
The improved FCM algorithm applied with the region fitting term of CV model, working as the reliance of evolving the level-set curve.
再将改进后的FCM算法应用到CV模型的区域检测项，可较准确地使像素点归类，以此作为曲线的演化依据。
The conventional FCM algorithm is noise sensitive because of not taking into account the spatial information and the relevant of pixel.
传统的FCM算法对原始图像进行分割，既没有考虑像素间相关性，又没有考虑像素的空间信息，因而对噪声十分敏感而且速度慢。
Then, it implements the data association and continuous tracking on the target candidates by using the particle filter and the FCM algorithm.
然后利用基于粒子滤波和FCM的算法实现对候选目标的数据关联和连续跟踪。
An explanation of membership degree in FCM algorithm from geometry view is given, which is helpful to understand the essence of FCM algorithm.
本文从几何角度给出模糊c均值聚类算法中隶属度的解释，这种解释能更好的说明模糊c均值聚类算法的本质。
To avoid the shortcomings of FCM and Particle Swarm Optimization algorithm, new hybrid clustering algorithm based on PSO and FCM algorithm is proposed.
针对模糊c均值算法与粒子群算法的不足，提出了一种基于粒子群算法和模糊c—均值算法的混合聚类算法。
The experiment results show that, KFCM-II algorithm is not better than FCM algorithm when applied to segment MRI images with low level degraded conditions;
实验结果表明，KFCM-II算法对低退化条件的MRI图像的分割任务，结果并不能比FCM算法占优；
It is indicated by experiments that the improved FCM algorithm has better distribution feature of membership values and enhances the precision of image processing.
实验表明，改进的FCM算法具有良好的隶属信息分布特性并提高了图像处理的精度。
A modified FCM algorithm for fire image segmentation is proposed in this paper based on the study of fuzzy clustering algorithm and characteristics of fire images.
本文在研究模糊聚类算法和火灾图像特点的基础上，提出了一种基于改进FCM算法的彩色火灾图像分割方法。
The new algorithm is applied to synthetic and real images and is shown to be effective and more robust to noise and other artifacts than the standard FCM algorithm.
人造图像和实际图像的实验结果表明该方法的有效性和对噪声具有较强的鲁棒性。
Then, expounds the theory of fuzzy set and fuzzy clustering, goes into details for the classical FCM algorithm, with a analysis for its performance and shortcomings.
接着阐述了模糊理论与模糊聚类的相关内容，详细介绍了经典的FCM算法，分析了它的性能及缺点。
In the paper, a suppressed fuzzy c-means (S-FCM) algorithm, for intensity image segmentation, is proposed on the basis of the characters of FCM algorithm and intensity images.
该文根据FCM算法和灰度图像的特点，提出了一种适用于灰度图像分割的抑制式模糊C -均值聚类算法(S - FCM)。
In this paper, an improved FCM algorithm (CFCM) is given, through which the lost information of in-complete-data images can be restored, while edge-detection of images is accomplished.
本文利用改进的模糊聚类算法，依据邻域信息实现了对丢失图像信息的恢复，并完成了对该图像的检测。
This algorithm has overcome the disadvantage of FCM algorithm effectively; meanwhile, it has enhanced the capability of overall searching and local optimum jumping from APSO algorithm.
新算法有效的克服了FCM算法的缺点，同时增强了APSO算法全局搜索和跳出局部最优的能力。
In the algorithm, the UK-GMPHDF is used to complete local state estimation of local sensors, then the FCM algorithm is used to fuse the local state estimation and result global state estimation.
用UK -GMPHDF完成局部传感器的局部状态估计，然后用FCM算法对这些局部状态进行融合处理，产生目标的全局状态估计。
Based on the systematic research of FCM and manufacturing cell formation, the fuzzy set based manufacturing cell formation algorithm SDFCM is put forward.
在系统研究f CM算法及制造单元构建问题的基础上，提出了基于模糊技术的制造单元构建方法SDFCM。
In the image analysis, FCM clustering algorithm can be effectively used for image processing, especially for hand-written numeral recognition.
在图像分析处理中，FCM聚类算法可以有效地用于图像处理，特别是手写数字识别中。
With the clustering feature analyzed, restrained function and pattern similarity are introduced. Then the algorithm of improved FCM is presented.
通过对模糊c均值算法聚类特性的分析，引入了约束函数及模式相似度的概念，提出了改进的FCM算法。
The fuzzy c-means algorithm (FCM) is one of widely used clustering algorithms.
模糊c均值算法(FCM)是经常使用的聚类算法之一。
The fuzzy c-means algorithm (FCM) is one of widely used clustering algorithms.
模糊c均值算法(FCM)是经常使用的聚类算法之一。
应用推荐