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Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a(More)
If there are more clusters than the ideal, each intrinsic cluster will be split into several subsets. Theoretically, this split can be arbitrary and neighboring data points have a certain probability to be co-located into same cluster. Based on this observation, a method using evidence accumulation through majority voting scheme with the k-means algorithm(More)
The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a(More)
Selective androgen receptor modulators (SARMs) are androgens with tissue-selective activity. SARMs that have anabolic activity on muscle while having minimal stimulatory activity on prostate are classified as SARM agonists. They can be used to prevent the loss of lean body mass that is associated with cancer, immunodeficiency, renal disease and aging. They(More)
Remote sensing provides huge multi-temporal data for earth surface, which has not been used completely. In the study, based on Visual C++ and Geographic Information System (GIS) platform, a multi-temporal data processing system using Grey Model (GM) is developed. By the interactive system, some functions, such as data input/output, visualization,(More)
— Data clustering is very useful in helping users visit the large scale of data in digit library. In this paper, we present an improved algorithm for clustering large scale of data set with dense relationship based on Affinity Propagation. First, the input data are divided into several groups and Affinity Propagation is applied to them respectively. Results(More)
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