Method for object segmentation based on deep-learning using a trained neural network and system for performing the same

A computer-readable recording medium in which a program for performing a method for object segmentation using a trained neural network is stored, wherein the method includes:

• receiving a target image, splitting the target image into unit images of a predetermined size, generating a unit activation map for each unit image as a first segmentation result by applying the neural network, merging the unit activation maps into a merged activation map in a first process, and outputting a second segmentation result based on the merged activation;
• and
• generating an entire activation map for the original target image by using the same neural network shared with the first process in a second process,
• wherein the neural network is trained by defining a loss function comprising a first loss term representing the difference between the entire activation map from the second process and the ground truth segmentation, a second loss term representing the difference between the merged activation map from the first process and the ground truth segmentation, and a third loss term representing the difference between the entire activation map from the second process and the merged activation map from the first process.