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Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimiza...
Nowadays, there are so many increasing amount of information within world-wide web. For these increasing amounts of information, we need efficient and effective index structure when we have to find ne...
Mammographic density is an important risk factor for breast cancer, detecting and screening at an early stage could help save lives. To analyze breast density distribution, a good segmentation algorit...
The devastating complexity of decision making in severe dynamic competitive environment of the universe, has forced the wise managers to have relevant strategic plans for their firms. In this paper, a...
This article is an addendum to the 2001 paper [1] which investigated an approach to hierarchical clustering based on the level sets of a density function induced on data points in a d-dimensional feat...
提出一种利用核模糊C均值聚类(KFCM)和改进分水岭算法分割猪肉眼肌切面图像中背最长肌区域的方法。该算法对经中值滤波去噪后图像的R分量利用最大方差自适应阈值(OTSU)去除背景,再采用KFCM提取出肌肉组织,然后进行空洞填充,最后由改进的分水岭算法分割出背最长肌区域。利用该算法对采集的60幅猪肉眼肌图像进行处理,分割正确率为86.67%;与传统的形态学算法相比,该算法能真实、完整地恢复出背最长肌区...
为了解决K-均值算法对农业图像中常用的超绿特征2G—R—B图像分割效果不佳的缺点,提出一种基于微粒群与K均值算法的图像分割方法。先用K均值算法对图像进行快速分类,然后将分类结果作为其中一个微粒的结果,利用微粒群算法计算,最后用K-均值算法在新的分类基础上计算新的聚类中心,更新当前的位置,以得到最优的图像分割阈值。试验结果表明,改进算法对超绿特征2G—R—B图像能够准确分割目标,且对不同类型的农业超...
Collaborative platform on clustering applications for governments consists of six large-scale systems, including the clustering Government Internet portal system, clustering public-mailboxes collabora...
This paper presents a new approach to image compression based on fuzzy clustering. This new approach includes pre-filtering, and fuzzy logic image enhancing to reduce undesirable noise effects on segm...
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our ...
This paper presents a subspace SVM ensemble algorithm for adaptive relevance feedback (RF) learning. Our method deals with the case that user’s relevance feedback examples are usually insufficient and...
AbstractIn recent years, the explosively growing amount of data in numerous clustering tasks has attracted considerable interest in boosting the existing clustering algorithms to large datasets. In th...
AbstractIn Mobile Ad Hoc Networks (MANET), network partitioning can cause sudden and severe disruptions to ongoing data accesses, and consequently data availability is decreased. A new distributed clu...
A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is ...
The aim is to facilitate the application of user defined constraints to the genetic clustering algorithm. This is achieved by presenting a general penalty function. The penalty function is defined as ...

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