Machine learning is a popular topic in data analysis and modeling. Many different machine
learning algorithms have been developed and implemented in a variety of programming …

In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

Fuzzy logic refers to a large subject dealing with a set of methods to characterize and
quantify uncertainty in engineering systems that arise from ambiguity, imprecision, fuzziness …

Algorithms for clustering data | Guide books skip to main content ACM Digital Library home
ACM home Google, Inc. (search) Advanced Search Browse About Sign in Register …

The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …

Now in its fifth edition, John C. Russ's monumental image processing reference is an even
more complete, modern, and hands-on tool than ever before. The Image Processing …

Word sense disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AI-complete problem, that is, a task …

Image Processing, Analysis and Machine Vision represent an exciting part of modern
cognitive and computer science. Following an explosion of inter est during the Seventies …

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of
pattern recognition to ensemble feature selection, now in its second edition The art and …

The problem of rotation-, scale-, and translation-invariant recognition of images is discussed.
A set of rotation-invariant features are introduced. They are the magnitudes of a set of …