Method of executing class classification processing using machine learning model, information processing device, and non-transitory computer-readable storage medium storing computer program

An information processing device configured to execute class classification processing relating to M classes using a machine learning model including a vector neural network including a plurality of vector neuron layers, where M is an integer equal to or greater than 2, the information processing device comprising:

• a memory configured to store the machine learning model;
• and
• a processor configured to execute a calculation using the machine learning model, wherein
• the processor is configured to execute processing of:
• (a) reading out, from the memory, N pieces of input data generated from one target object, where N is an integer equal to or greater than 2;
• (b) inputting each of the N pieces of input data to the machine learning model, and obtaining, for each of the N pieces of input data, M classification output values that are output from an output layer of the machine learning model, one classified class, and a feature spectrum that is obtained from an output of a specific layer of the machine learning model;
• (c) obtaining a similarity degree between a known feature spectrum group and the feature spectrum for each of the N pieces of input data, the known feature spectrum group being obtained from the output of the specific layer when a plurality of pieces of teaching data are input to the machine learning model, and obtaining, for each of the N pieces of input data, a reliability degree with respect to the classified class as a function of the similarity degree;
• and
• (d) executing, for each of the N pieces of input data, a vote for the classified class, based on the reliability degree with respect to the classified class, and determining a class determination result for the target object, based on a result of the vote.

A non-transitory computer-readable storage medium storing a computer program for causing a processor to execute class classification processing relating to M classes using a machine learning model including a vector neural network including a plurality of vector neuron layers, where M is an integer equal to or greater than 2, the computer program for causing the processor to execute processing of:

• (a) reading out, from a memory, N pieces of input data generated from one target object, where N is an integer equal to or greater than 2;
• (b) inputting each of the N pieces of input data to the machine learning model, and obtaining, for each of the N pieces of input data, M classification output values that are output from an output layer of the machine learning model, one classified class, and a feature spectrum that is obtained from an output of a specific layer of the machine learning model;
• (c) obtaining a similarity degree between a known feature spectrum group and the feature spectrum for each of the N pieces of input data, the known feature spectrum group being obtained from the output of the specific layer when a plurality of pieces of teaching data are input to the machine learning model, and obtaining, for each of the N pieces of input data, a reliability degree with respect to the classified class as a function of the similarity degree;
• and
• (d) executing, for each of the N pieces of input data, a vote for the classified class, based on the reliability degree with respect to the classified class, and determining a class determination result for the target object, based on a result of the vote.