Method for selecting training data to train a deep learning model and training data selecting device using the same

Abstract

A method for selecting training data for training a deep learning model is provided. The method includes steps of: (a) obtaining one or more individual attributes each of which corresponds to each of a plurality of training data included in total training data, and generating a bipartite graph by matching each of the plurality of training data included in the total training data with the individual attributes; and (b) selecting n training data among the total training data, by referring to the bipartite graph, wherein the n is a target number of the training data to be used for training the deep learning model, and wherein the training data selecting device selects the n training data to be used for training the deep learning model such that each cardinal number of each of the individual attributes matched with the n training data is within a predetermined deviation threshold.