Our fuzzy classifier detects classes of image pixels corresponding to gray level variation in the various directions. It uses an extended Epanechnikov function as a fuzzy set membership functionâ€¦ (More)

We investigate a method to speed up the O(n) labeling algorithm of Rosenfeld and Pfaltz for segmenting binary images, which is unduly complex for large images. That algorithm searches line-by-line,â€¦ (More)

We survey research of recent years on the supervised training of feedforward neural networks. The goal is to expose how the networks work, how to engineer them so they can learn data with lessâ€¦ (More)

We develop an integrated multi-phase approach to middle and high level data fusion with an application to situation and threat assessments. The method first builds a feature vector for each detectedâ€¦ (More)

Some major problems in clustering are: i) find the optimal number K of clusters; ii) assess the validity of a given clustering; iii) permit the classes to form natural shapes rather than forcing themâ€¦ (More)

A model is described that uses Boolean rule matrices that are equivalent to implication digraphs to transform truth states associated with rule conditions into deduced or abduced truth states. Suchâ€¦ (More)