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The paper presents a fuzzy c-means clustering based fuzzy measure for weighting samples in a dataset for pattern classification. The method improves classification efficiency. The fuzzy c-means generated membership grades of a sample for belonging to different clusters are interpreted as measures of uncertainty for assigning specific crisp class label to this sample. The fuzzy measure of total uncertainty...
Image segmentation is often regarded as the first and most important step for other higher level image interpretation, e.g. information extraction and image mining. Although a lot of researches have dedicated to this field, due to its intrinsic dilemma, there exist a wide range of shortcomings of current segmentation methods. When applied to remotely sensed imagery which are commonly with tremendous...
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