US 12,118,438 B2
Learning data generation device, learning data generation method, and program
Yuki Kurauchi, Musashino (JP); Naoto Abe, Musashino (JP); Hiroshi Konishi, Musashino (JP); and Hitoshi Seshimo, Musashino (JP)
Assigned to NIPPON TELEGRAPH AND TELEPHONE CORPORATION, Tokyo (JP)
Appl. No. 17/270,862
Filed by NIPPON TELEGRAPH AND TELEPHONE CORPORATION, Tokyo (JP)
PCT Filed Sep. 9, 2019, PCT No. PCT/JP2019/035346
§ 371(c)(1), (2) Date Feb. 24, 2021,
PCT Pub. No. WO2020/059556, PCT Pub. Date Mar. 26, 2020.
Claims priority of application No. 2018-176174 (JP), filed on Sep. 20, 2018.
Prior Publication US 2021/0201204 A1, Jul. 1, 2021
Int. Cl. G06N 20/00 (2019.01)
CPC G06N 20/00 (2019.01) 19 Claims
OG exemplary drawing
 
1. A training data generation device comprising:
a processor configured to
correct training data that is time-series data that indicates states of an object and in which a label corresponding to a state of the object is assigned to each section that corresponds to the state indicated by the label,
wherein the processor corrects a break time that divides a first section from a second section adjacent to the first section, based on time-series data in the first section and time-series data in the second section,
the processor corrects the break time so as to maximize a sum of a difference between an average of the time-series data in the first section and an average of the time-series data in the second section and a difference between a variance of the time-series data in the first section and a variance of the time-series data in the second section, and
the training data, after correction, is used to train a model that estimates and outputs a condition of a road surface corresponding to the training data.