Title:
MATERIAL PROPERTY VALUE PREDICTION METHOD, TRAINED MODEL GENERATION METHOD, PROGRAM, AND DEVICE
Document Type and Number:
WIPO Patent Application WO/2023/189006
Kind Code:
A1
Abstract:
The present invention improves the accuracy of prediction of a property value of a material. A method according to an embodiment of the present invention acquires an image of a material, and performs a topological data analysis on the image of the material, to thereby extract a feature of the material and predict a property value of the material from the feature of the material.
Inventors:
YAMAGUCHI SATOSHI (JP)
IMAZATO SATOSHI (JP)
HOKII YUSUKE (JP)
AKIYAMA SHIGENORI (JP)
FUSEJIMA FUTOSHI (JP)
IMAZATO SATOSHI (JP)
HOKII YUSUKE (JP)
AKIYAMA SHIGENORI (JP)
FUSEJIMA FUTOSHI (JP)
Application Number:
PCT/JP2023/006045
Publication Date:
October 05, 2023
Filing Date:
February 20, 2023
Export Citation:
Assignee:
UNIV OSAKA (JP)
G C DENTAL IND CORP (JP)
G C DENTAL IND CORP (JP)
International Classes:
G16C60/00; G01N23/2251; G01N33/00; G06T7/00
Foreign References:
| JP2019179319A | 2019-10-17 | |||
| US20090087070A1 | 2009-04-02 |
Other References:
HIRAOKA YASUAKI, IPPEI OBAYASHI, KAZUTO AKAGI : "Persistent Homology and Structural Analysis in Materials Science", JOURNAL OF JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE, vol. 34, no. 3, 1 May 2019 (2019-05-01), pages 330 - 338, XP093095274, ISSN: 2188-2266
Attorney, Agent or Firm:
ITOH, Tadashige et al. (JP)
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