Algorithms and theoretical analysis
Mathematical evaluation of pattern recognition problems, fitting, effect of noise, treatment of multiple scattering, theoretical limits, etc.
Parallel and/or discrete pattern recognition
Includes Hough transform approaches, look-up tables, associative memory.
Neural networks, machine learning, and neuromporhic approaches
Includes both software/firmware implementations and exploration of neuromorphic hardware
Applications and performance evaluation
Examples of implemented pattern recognition problems and solutions with emphasis on new challenges and limits of scaling existing approaches.