The present disclosure relates to an artificial intelligence (AI) system that simulates functions such as cognition and judgment of the human brain by utilizing machine learning algorithms such as deep learning and its application. In particular, the present disclosure is a hierarchical learning method of a neural network according to an artificial intelligence system and its application, and generates a first activation map by applying a source learning image to a first learning network model set to generate semantic segmentation, and generates semantic segmentation. A second activation map is generated by applying the source learning image to the second learning network model set to generate the second activation map, and based on the first activation map and the second activation map, a loss is calculated from the labeled data of the source learning image, The weights of the plurality of network nodes constituting the first learning network model and the second learning network model may be updated based on the loss.
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