title: Neural network feature detector for real-time video signal processing.
abstract: The application of artificial neural networks to real-time image processing tasks requires the use of dedicated, high performance hardware. A linear array processor called HANNIBAL has been developed which implements the backpropagation neural learning algorithm on-chip. This paper considers the design of a complete neural system which integrates HANNIBAL into an existing image processing environment. The goals for the design of the system have been set partly by the primary application, namely feature recognition, but mainly by the desire for a flexible, high performance hardware tool for the study and evaluation of range of neural image processing applications.
authors.affiliation: Department of Electronic and Electrical Engineering, Loughborough University of Technology, Leicestershire, England.
authors.forename: D
authors.initials: D
authors.lastname: Naylor
authors.forename: S
authors.initials: S
authors.lastname: Jones
authors.forename: D
authors.initials: D
authors.lastname: Myers
authors.forename: J
authors.initials: J
authors.lastname: Vincent
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003071:Cognition; D003199:Computer Systems; D003201:Computers; D005145:Face; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D016571:Neural Networks, Computer; D012984:Software