Recognizing complex patterns.
How the brain recognizes complex patterns in the environment is a central, but little understood question in neuroscience. The problem is of great significance for a host of applications such as biometric-based access control, autonomous robots and content-based information management. Although some headway in these directions has been made, the current artificial systems do not match the robustness and versatility of their biological counterparts. Here I examine recognition tasks drawn from two different sensory modalities--face recognition and speaker/speech recognition. The goal is to characterize the present state of artificial recognition technologies for these tasks, the influence of neuroscience on the design of these systems and the key challenges they face.
Sinha
Pawan
P
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. sinha@ai.mit.edu
D000818:Animals; D001185:Artificial Intelligence; D001921:Brain / Q000502:physiology*; D005145:Face; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000639:trends*; D009488:Neurosciences / Q000639:trends*; D010364:Pattern Recognition, Visual / Q000502:physiology*; D013067:Speech Perception / Q000502:physiology*