METHOD FOR IMPROVING THE ACCURACY OF A CONVOLUTION NEURAL NETWORK TRAINING IMAGE DATA SET FOR LOSS PREVENTION APPLICATIONS

摘要

Techniques for improving the accuracy of a neural network trained for loss prevention applications include identifying physical features of an object in image scan data, cropping indicia from the image scan data, and examining physical features in the indicia-removed image scan data using a neural network to identify the object based on comparison of identification data based on the physical features and other identification, such as based on the indicia. In response to a match prediction, indicating a match and generating an authenticating signal.