Fish Inspection System Using a Parallel Neural Network Chip and the Image Knowledge Builder Application

A generic image learning system, CogniSight, is being used for the inspection of fishes before filleting offshore. Each CogniSight system uses four neural network chips (a total of 312 neurons) based on a natively parallel, hard-wired architecture that performs real-time learning and nonlinear classification (RBF). These systems are trained by the ship crew using Image Knowledge Builder, a "show and tell" interface that facilitates easy training and validation. The fast and high return of investment (ROI) to the fishing fleet has significantly increased the market share of Pisces Industries, the company integrating CogniSight systems to its filleting machines.