Method for auto-labeling training images for use in deep learning network to analyze images with high precision, and auto-labeling device using the same

An auto-labeling device for auto-labeling one or more training images to be used for learning a neural network, comprising:

• at least one memory that stores instructions;
• and
• at least one processor configured to execute the instructions to perform processes of (I) if a specific training image among the training images is acquired, instructing a meta ROI detection network to generate at least one feature map by applying one or more convolution operations to the specific training image and then instructing the meta ROI detection network to acquire n current meta ROIs corresponding to regions of objects by referring to the at least one feature map, on the specific training image, wherein the objects are grouped on the feature map according to each of locations of each of the objects on the specific training image by referring to the feature map, and wherein the n is an integer same as or larger than 1, and (II) generating n manipulated images by cropping regions, corresponding to the n current meta ROIs, on the specific training image, instructing an object detection network to output each of n labeled manipulated images having each of bounding boxes for each of the n manipulated images, and generating a labeled specific training image by merging the n labeled manipulated images.