Methods for training auto-labeling device and performing auto-labeling by using hybrid classification and devices using the same

Abstract

A method for training an auto-labeling device is provided. The method includes: (a) inputting a training image to a feature extraction module to generate a feature, (b) inputting the feature to a fitness estimation module to output a fitness value, inputting the feature to a first classification module to output a first class score and a first uncertainty score, inputting the feature to a second classification module to output a second class score and a second uncertainty score, and then generating a scaled second uncertainty score; and (c) (i) training the first classification module and the feature extraction module by referring to the first class score, (ii) training the second classification module and the feature extraction module by referring to the second class score, (iii) updating a scale parameter by referring to the first uncertainty score and the scaled second uncertainty score, and (iv) training the fitness estimation module.