• Examines the use of neural nets to automatic target recognition
• Explores how self-organizing maps (SOMs) serve as a powerful tool in clustering, dimensionality reduction
• Introduces VIEWNET - self-organizing architecture for recognizing 3-D objects from sequences of their 2-D views
• Discusses the use of Hopfield networks
• Profiles the contributions from international experts

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:

• shape recognition
• shape from shading
• aircraft detection in SAR images
• visualization of high-dimensional data bases of industrial systems
• 3-D object learning and recognition from multiple 2-D views
• fingerprint classification
• performance optimization in flexible manufacturing systems

The remaining chapters address issues and applications in the expansive area of multimedia communications as well as mobile and cellular communications.