01-03-2009, 01:34 PM
FACE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS
Artificial Neural Networks commonly referred to as ËœNeural Networksâ„¢ is a new branch of AI, that enabled a crude simulation of the structure of human brain electronically or in software. The inherent properties of human brain enable it to analyze complex patterns consisting of a number of elements, those individually reveal little of the total pattern, yet collectively represent easily recognizable objects.
The concepts of Neural Networks have been motivated right from its inception, by the recognition that the human brain computes in an entirely different way from the conventional digital computers. The brain modeling techniques opens a new era of Computer System that learns, from experience and uses its experiential knowledge next time. This biologically inspired method is being touted as the wave of the future in computing, relieving the programmer from the cubicle of traditional algorithmic problem solving. Inherent non-linearity property of Neural Networks makes it particularly suitable in many signal-processing applications like sound, image processing etc.
Artificial Neural Networks commonly referred to as ËœNeural Networksâ„¢ is a new branch of AI, that enabled a crude simulation of the structure of human brain electronically or in software. The inherent properties of human brain enable it to analyze complex patterns consisting of a number of elements, those individually reveal little of the total pattern, yet collectively represent easily recognizable objects.
The concepts of Neural Networks have been motivated right from its inception, by the recognition that the human brain computes in an entirely different way from the conventional digital computers. The brain modeling techniques opens a new era of Computer System that learns, from experience and uses its experiential knowledge next time. This biologically inspired method is being touted as the wave of the future in computing, relieving the programmer from the cubicle of traditional algorithmic problem solving. Inherent non-linearity property of Neural Networks makes it particularly suitable in many signal-processing applications like sound, image processing etc.