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K-nearest neighbor (KNN) is a common classification method for data mining techniques. It has been widely used in many fields because of the implementation simplicity, the clarity of theory and the excellent classification performance. But KNN will increase classification error rate when training samples distribute unevenly or sample number of each class is very different. So, learning from the idea...
Data mining is the analysis of large observational data sets to find unsuspected relationships and to summarize the data. With the development of the broadcasting and television monitoring, monitoring data in database have become more and more. People hope that these data are both understandable and useful to future work. Therefore, it is very significant to discuss the specific applications of data...
Many facial image analysis methods rely on learning-based techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and Gabor filters) from large sets of training data. In general, the learning process consists of selecting discriminative image filters from a large feature pool that contains filters uniformly sampled from the parameter space...
For Internet based video broadcasting applications such as IPTV, the peer-to-peer (P2P) streaming scheme has been found to be an effective solution. An important issue in live broadcasting is to avoid playback buffer underflow. How to utilize the playback buffer and upload bandwidth of peers to minimize the freeze-ups in playback, is the problem we try to solve. In this work, we propose a successive...
We use high resolution image of ASTER to extract glacier, during the extraction, based on the methods of glacier extraction before, we make up a set of glacier extraction work flow combined with the research area and research data. As a result, it is proved that the accuracy of the glacier extraction is high, and achieve the need of the research, on the other hand, we research the debris classification...
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