Ajou University Industry-Academic Cooperation Foundation

Incheon National University Research & Buisness Foundation

Hyeon Cho

Won Jun Hwang

Hyung Ho Kim

Ouk Choi

Provided is a method of training a generative adversarial network (GAN) for converting between heterogeneous domains, the method including training a first GAN and a second GAN with at least one unpaired training data set comprised of a training image of a first domain and a training image of a second domain; using the trained first GAN to convert a first image of the first domain to an image of the second domain; using the trained second GAN to reconvert the converted image of the second domain to a second image of the first domain; and performing segmentation on at least one of the first image of the first domain, the converted image of the second domain, or the reconverted second image of the first domain.

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Jeollanam-do, South Korea

Hyeon Cho