US 11,922,307 B2
Learning device, inference device, and learned model
Kosuke Nakago, Tokyo (JP); Daisuke Motoki, Tokyo (JP); Masaki Watanabe, Tokyo (JP); Tomoki Komatsu, Tokyo (JP); Hironori Moki, Hokkaido (JP); Masanobu Honda, Miyagi (JP); Takahiko Kato, Miyagi (JP); and Tomohiko Niizeki, Miyagi (JP)
Assigned to Preferred Networks, Inc., Tokyo (JP); and Tokyo Electron Limited, Tokyo (JP)
Filed by Preferred Networks, Inc., Tokyo (JP); and Tokyo Electron Limited, Tokyo (JP)
Filed on Mar. 2, 2021, as Appl. No. 17/189,608.
Application 17/189,608 is a continuation of application No. PCT/JP2019/033168, filed on Aug. 23, 2019.
Claims priority of application No. 2018-164931 (JP), filed on Sep. 3, 2018.
Prior Publication US 2021/0209413 A1, Jul. 8, 2021
Int. Cl. G06N 3/08 (2023.01); G06F 18/214 (2023.01); G06N 3/04 (2023.01); G06T 7/00 (2017.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 10/32 (2022.01)
CPC G06N 3/08 (2013.01) [G06F 18/214 (2023.01); G06N 3/04 (2013.01); G06T 7/0004 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 2207/20084 (2013.01); G06T 2207/30148 (2013.01); G06V 10/32 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An inference method performed by at least one processor, the method comprising:
inputting, by the at least one processor, into a learned model, non-processed object image data of a second object and data related to a second process for the second object, and
inferring, by the at least one processor using the learned model, processed object image data of the second object on which the second process has been performed,
wherein the learned model has been trained so that an output obtained in response to non-processed object image data of a first object and data related to a first process for the first object being input approaches processed object image data of the first object on which the first process has been performed.