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Adaptive clustering is one of the common methods in wireless sensor networks to prolong the network lifetime. Single-hop dynamic clustering proposed in LEACH protocol is simple and energy-efficient. By random clustering, it causes uneven energy consumption and terrible energy consumption when sink node is far away from the network. We develop a protocol called TCMR (Twice Clustering and Multi-hop...
In recent years, the Bag-of-visual Words image representation has led to many significant results in visual object recognition and categorization. However, experiments show that the unsupervised clustering of primitive visual features tends to result in the limited discriminative ability of the visual codebook, since it does not take the spatial relationship between visual primitives into consideration...
For applications of data mining techniques in geosciences, through mining spatial databases which are constructed with geophysical and geochemical data measured in fields, the knowledge, such as the spatial distribution of geological targets, the geophysical and geochemical characteristics of geological targets, the differentiation among the geological targets, and the relationship among geophysical...
For applications of clustering algorithms, the key techniques are to handle complicatedly distributed clusters and process massive data effectively and efficiently. On the basis of analysis and research of traditional clustering algorithms, a clustering algorithm based on density and adaptive density-reachable is presented in this paper, which can handle clusters of arbitrary shapes, sizes and densities...
Three clustering methods are presented and discussed by experimental analysis. The results by using three clustering methods which are partitioning methods, hierarchical methods and density-based methods visually illustrate the clustering results, in two-dimensional data sets as experimental data are used. Clearly, when the original data set is spherical shape, most of the cluster methods can get...
For applications of clustering algorithms, a key technique is to handle complicatedly distributed clusters effectively and efficiently. On the basis of analysis and research of traditional clustering algorithms, a clustering algorithm based on density and adaptive density-reachable is presented in this paper. Experimental results show that the algorithm can handle clusters of arbitrary shapes, sizes...
Texts in web pages, images and videos contain important clues for information indexing and retrieval. Most existing text extraction methods depend on the language type and text appearance. In this paper, a novel and universal method of image text extraction is proposed. A coarse-to-fine text location method is implemented. Firstly, a multi-scale approach is adopted to locate texts with different font...
In this paper, we present a novel framework for video semantic detection based on transductive inference and hierarchical clustering, which directly focuses on predicting the available samples in a current unlabeled pool, instead of trying to build a classifier workable for any unavailable data. In this framework, a number of hierarchical clustering results are constructed from the entire video dataset ...
Using CABOFSV to cluster, whether b, the beginning parameter, threshold value of set-square-difference, also named up-bound of a cluster, is reasonable or not is fatal to clustering results. In this paper, how to determine the threshold value of set-square-difference in CABOSFV algorithm is deeply studied. Then, the method of how to determine threshold value of set-square-difference is put forward...
The document image segmentation is an important component in the document image understanding. kernel-based methods have demonstrated excellent performances in a variety of pattern recognition problems. This paper applies kernel-based methods and Gabor wavelet to the document image segmentation. The feature image are derived from Gabor filtered images. Taking the computational complexity into account,...
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