Title:
ディープラーニングに基づいた自動車部位別の破損程度の自動判定のためのモデル学習方法およびシステム
Document Type and Number:
Japanese Patent JP7300765
Kind Code:
B2
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.
Inventors:
Kim, Taeyun
Oh, Jin Sol
Bae, Byung Sung
Oh, Jin Sol
Bae, Byung Sung
Application Number:
JP2021536349A
Publication Date:
June 30, 2023
Filing Date:
December 30, 2019
Export Citation:
Assignee:
Agile Soda Incorporated
International Classes:
G06T7/00; G06N3/0464; G06Q10/20; G06V10/82
Domestic Patent References:
| JP2018537798A |
Foreign References:
| WO2018191435A1 |
Attorney, Agent or Firm:
▲吉▼川 俊雄
Hiroshi Ichikawa
Hiroshi Ichikawa