Hierarchical clustering is used widely to organize data and search for patterns. Previous algorithms assume that the body of data being clustered is fixed while the algorithm runs...
H. Van Dyke Parunak, Richard Rohwer, Theodore C. B...
Often the most expensive and time-consuming task in building a pattern recognition system is col lecting and accurately labeling training and testing data. In this paper, we exp...
This paper presents a new approach including passive and actriveprocesses to deal with the image segmentation and pattern recognition to a color blindness plate (CBP). The CBP is ...
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
A similarity measure is described that does not require the prior specification of features or the need for training sets of representative data. Instead large numbers of feature...