Industrial Applications of Neural Networks explores the success of neural networks in different areas of engineering endeavors. Each chapter shows how the power of neural networks can be exploited in modern engineering applications.
The first seven chapters focus on image processing as well as industrial or manufacturing perspectives. Topics discussed include:
The remaining chapters address issues and applications in the expansive area of multimedia communications as well as mobile and cellular communications.
On-Line Shape Recognition with Incremental Training Using Neural Networks with Binary Synaptic Weights, F. Ulgen, N. Akamatsu, and M. Fukumi - Japan
Neural Network Approaches to Shape from Shading, G.Q. Wei and G. Hirzinger - Germany
Neural Networks and Fuzzy Reasoning to Detect Aircraft in SAR Images, A. Filippidis, L.C. Jain, and N.M. Martin - Australia
The Self-Organising Map in Industry Analysis, O. Simula, P. Vasara, J. Vesanto, and R.R. Helminen - Finland
A Self-Organizing Architecture for Invariant 3-D Object Learning and Recognition from Multiple 2-D Views, S. Grossberg and G. Bradski - United States
Industrial Applications of Hierarchical Neural Networks: Character Recognition and Finger Print Classification, U. Halici, A. Erol, and G. Ongun - Turkey
Neural Networks for Performance Optimization in Flexible Manufacturing Systems, S. Cavalieri - Italy
Channel Assignment in Mobile Communication Networks - A Computational Intelligence Approach, G. Wang and N. Ansari - United States
Application of Cellular Compact Neural Networks in Digital Communications, B.J. Sheu, M.Y. Wang, and W.C. Young - United States
Neural Networks for Process Scheduling in Communications Systems, S. Cavalieri and O. Mirabella - Italy