Abstract: The present invention relates to a deep-learning based system and method of automatically determining a degree of damage to each area of a vehicle, which is capable of quickly calculating a consistent and reliable quote for vehicle repair by analyzing an image of a vehicle in an accident by using a deep learning-based Mark R-CNN framework and then extracting a component image corresponding to a damaged part, and automatically determining the degree of damage in the extracted component image based on a pre-trained model.

Abstract: The present invention relates to a deep-learning based system and method of automatically determining a degree of damage to each area of a vehicle, which is capable of quickly calculating a consistent and reliable quote for vehicle repair by analyzing an image of a vehicle in an accident by using a deep learning-based Mark R-CNN framework and then extracting a component image corresponding to a damaged part, and automatically determining the degree of damage in the extracted component image based on a pre-trained model.

Abstract: The present invention relates to a method and a system for training a model for automatically determining the degree of damage for each vehicle area based on deep learning, which generate a model capable of quickly calculating a consistent and reliable vehicle repair quote by learning so as to automatically extract a picture in which it is possible to determine the degree of damage among accident vehicle pictures by using the Mask R-CNN framework and the Inception V4 network structure based on deep learning, and learning the degree of damage for each type of damage.