METHOD AND APPARATUS FOR LEARNING DEEP LEARNING MODEL FOR ORDINAL CLASSIFICATION PROBLEM BY USING TRIPLET LOSS FUNCTION

摘要

The present invention relates to image processing using machine learning, and a method for learning a deep learning model for an ordinal classification problem makes a learning object into an input; forms convolutional neural networks (CNNs) including a branch point and two end points, which are separated from a branch thereof so as to cause classification loss and triplet loss, calculates classification loss for end-to-end learning, calculates the triplet loss such that a network can learn ordinal characteristics, and updates the network for a final loss value by performing relative triplet sampling on the basis of the calculated classification loss and triplet loss, thereby enabling effective learning and loss control.