US 11,809,994 B2
Information processing apparatus, information processing method, and non-transitory computer-readable storage medium
Koichi Tanji, Kawasaki (JP)
Assigned to CANON KABUSHIKI KAISHA, Tokyo (JP)
Filed by CANON KABUSHIKI KAISHA, Tokyo (JP)
Filed on Aug. 4, 2020, as Appl. No. 16/984,448.
Claims priority of application No. 2019-149156 (JP), filed on Aug. 15, 2019.
Prior Publication US 2021/0049411 A1, Feb. 18, 2021
Int. Cl. G06N 3/084 (2023.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06N 3/02 (2006.01); G06V 10/44 (2022.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06F 18/21 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 10/94 (2022.01); G06N 3/045 (2023.01); G06F 18/2413 (2023.01); G06V 10/22 (2022.01); G06F 18/40 (2023.01)
CPC G06N 3/084 (2013.01) [G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/24 (2023.01); G06F 18/41 (2023.01); G06N 3/02 (2013.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06V 10/235 (2022.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 10/945 (2022.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20104 (2013.01)] 12 Claims
OG exemplary drawing
 
1. An information processing apparatus comprising:
a memory storing instructions; and
a processor that executes the instructions to:
obtain an output image output from a classifier that receives input data;
calculate a first error between the output image and a supervised image corresponding to the input data;
set a region of interest in the supervised image for calculating a topological invariant, which is a property that is kept unchanged even if an original shape is continuously transformed;
calculate a first topological invariant of the region of interest in the supervised image;
calculate a second topological invariant of a correspondence region in the output image corresponding to the region of interest;
calculate a second error between the first topological invariant and the second topological invariant;
calculate a total error from the first error and the second error; and
train the classifier to minimize the total error.