Real-Time 3-D Object Classification Using a Learning System
Raymond D. Rimey, P. Gouin, Christopher L. Scofield, Douglas L. Reilly · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1987
We describe some experiments in real-time 3-D object classification using a learning system derived from a general neural model for supervised learning. The primary advantages of the learning system are its ability to learn from experience to recognize patterns and its inherent massive parallelism. Our motivation is to examine the feasibility and merits of the learning system in a simple machine vision problem.