Clustering is the unsupervised classification of patterns (observations, data items, or feature
vectors) into groups (clusters). The clustering problem has been addressed in many …

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

… Prabhakar and AK Jain, “Decision-level fusion in fingerprint verification,” Pattern Recognit., …
Kumar, DC Wong, HC Shen, and AK Jain, “Personal verification using palmprint and hand …

Organizing data into sensible groupings is one of the most fundamental modes of
understanding and learning. As an example, a common scheme of scientific classification puts …

Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected
simple processors. The article discusses the motivations behind the development of …

Biometric recognition, or simply Biometrics, is a rapidly evolving field with applications ranging
from accessing one's computer to gaining entry into a country. Biometric systems rely on …

This paper proposes an unsupervised algorithm for learning a finite mixture model from
multivariate data. The adjective "unsupervised" is justified by two properties of the algorithm: 1) it …

We consider a texture to be a stochastic, possibly periodic, two-dimensional image field. A
texture model is a mathematical procedure capable of producing and describing a textured …

… Hong and Jain associate different confi dence measures with the individual matchers when
inte … Hong and AK Jain, "Integrating faces and finger prints for personal identification," IEEE …

… Jain and Dubes approach the validity problem from the viewpoint of probability and
statistics and begin by providing background information that includes fundamentals of …