公开(公告)号：US20240005655A1

公开(公告)日：2024-01-04

申请号：US18247493

申请日：2020-10-21

Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION

Inventor： Mihiro UCHIDA ,  Jun SHIMAMURA ,  Shingo ANDO ,  Takayuki UMEDA

IPC: G06V10/98 ,  G06V10/774 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/98 ,  G06V10/774 ,  G06V10/764 ,  G06V10/82

Abstract: A learning apparatus includes: a data generation unit that learns generation of data based on a class label signal and a noise signal; an unknown degree estimation unit that learns estimation of a degree to which input data is unknown using a training set and the data generated by the data generation unit; a first class likelihood estimation unit that learns estimation of a first likelihood of each class label for input data using the training set; a second class likelihood estimation unit that learns estimation of a second likelihood of each class label for input data using the training set and the data generated by the data generation unit; a class likelihood correction unit that generates a third likelihood by correcting the first likelihood on the basis of the unknown degree and the second likelihood; and a class label estimation unit that estimates a class label of data related to the third likelihood on the basis of the third likelihood, thereby automatically estimating a cause of an error by a deep model.

公开(公告)号：US20240281711A1

公开(公告)日：2024-08-22

申请号：US18548148

申请日：2021-03-23

Applicant: NIPPON TELEGRAPH AND TELEPHONE CORPORATION

Inventor： Mihiro UCHIDA ,  Takayuki UMEDA ,  Shingo ANDO ,  Jun SHIMAMURA

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: There is provided a class label estimation device that estimates a class label of input data and estimates a cause of an estimation error, the class label estimation device including: a distribution estimation unit that estimates a distribution followed by a training set; a distance estimation unit that estimates a distance of the input data from the training set based on the distribution; an unknown degree estimation unit that estimates an unknown degree of the input data based on the distance; an unknown degree correction unit that corrects the unknown degree based on the distribution; and an error cause estimation unit that estimates a cause of an estimation error using the corrected unknown degree.