Artificial neural networks (ANNs) are tools that are used to analyse information by emulating the biological nervous system and adaptive biological learning. ANNs are good pattern reoognition engines and robust classifiers. They may also be applied to control problems, and problems that are too complex for conventional technologies. ANNs complement other information analysis tools such as multivariate statistics, clustering algorithms, probabilistic modeling, fuzzy logic, expert or knowledge-based systems, signal processing, conventional image processing, Fourier analysis, and wavelet analysis. This CD collection includes papers on both the underlying science as well as the many applications of ANNs that have developed in the last decade. The papers were originally presented at the Conferences on Applications and Science of Artificial Neural Networks, a series that has been part of the SPIE Aerosense meeting since 1990. Long-time chair Steven K. Rogers has selected from these proceedings the papers that best represent the field.