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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...
Recently, bag of words (BoW) model has led to many significant results in visual object classification. However, due to the limited descriptive and discriminative ability of visual words, the resulting performance of visual object classification is still incomparable to its analogy in text domain, i.e. document categorization. Furthermore, for weakly labeled image data, where we only know whether...
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...
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