نتایج جستجو برای: clustering
تعداد نتایج: 102936 فیلتر نتایج به سال:
spike sorting is a class of techniques used in the analysis of electrophysiological data. studying the dynamics of neural activity via electrical recording relies on the ability to detect and sort neural spikes recorded from a number of neurons by the same electrode. this article reviews methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting.
Background: Microarray DNA technology has paved the way for investigators to expressed thousands of genes in a short time. Analysis of this big amount of raw data includes normalization, clustering and classification. The present study surveys the application of clustering technique in microarray DNA analysis. Materials and methods: We analyzed data of Van’t Veer et al study dealing with BRCA1...
energy consumption is considered as a critical issue in wireless sensor networks (wsns). batteries of sensor nodes have limited power supply which in turn limits services and applications that can be supported by them. an efcient solution to improve energy consumption and even trafc in wsns is data aggregation (da) that can reduce the number of transmissions. two main challenges for da are: (i)...
image segmentation is an essential issue in image description and classification. currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. moreover, there are many uncertainties and vagueness in images, which crisp clustering and even type-1 fuzzy clustering could not handle. hence, type-...
vehicular ad-hoc network (vanet) is an important component of intelligent transportation systems, in which vehicles are equipped with on-board computing and communication devices which enable vehicle-to-vehicle communication. consequently, with regard to larger communication due to the greater number of vehicles, stability of connectivity would be a challenging problem. clustering technique as ...
The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often being stuck at locally optimal values and therefore cannot converge to global optima solution. In this paper, we introduce several new variation operators for the proposed hybrid genetic algorithm for the cl...
Knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering in which there is no need to be peculiar about how to select initial values. Due to properly converting the task of optimization to an equivalent...
background: gastrointestinal tract cancer (gi.c) is one of the common cancers in world‑wide. the incidence rate of it is different in various geographical regions. this study was performed to assess spatial clusters of the occurrence of gi.c in fars province. methods: in this cross‑sectional study, the new cases were 4569 cases from 2001 to 2009. the crude incidence rates were standardized base...
Abstract: Due to the growth of digital images require efficient methods to annotate the images is sense. In this paper, a semi-supervised spectral clustering with relevance feedback is used to annotate digital photos which is overcome the local minima problem on clustering methods by using some labeled information given by users. Performance of the proposed method is tested on Corel 5K dataset ...
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