In recent years significant breakthroughs in exploring big data, recognition of complex
patterns, and predicting intricate variables have been made. One efficient way of analyzing …

We review more than 200 applications of neural networks in image processing and discuss
the present and possible future role of neural networks, especially feed-forward neural …

Over the past decade there have been considerable increases in both the quantity of
remotely sensed data available and the use of neural networks. These increases have …

Fuzzy classification techniques have been developed recently to estimate the class
composition of image pixels, but their output provides no indication of how these classes are …

Landscape pattern represents a key variable in management and understanding of the
environment, as well as driving many environmental models. Remote sensing can be used …

An object recognition approach based on concurrent coarse-and-fine matching using a
multilayer Hopfield neural network is presented. The proposed network consists of several …

Map** is essential for the analysis of the land use and land cover, which influence many
environmental processes and properties. For the purpose of the creation of land cover maps …

We present some new results which definitively explain thebehavior of the classical,
heuristic nonlinear relaxation labelingalgorithm of Rosenfeld, Hummel, and Zucker in terms …

Since the outstanding and pioneering research work of Hopfield on recurrent neural
networks (RNNs) in the early 80s of the last century, neural networks have rekindled strong …

The Hopfield network has been applied to the power system economic dispatch problem
with very promising results. However, it has been found that the unit commitment problem …