公开(公告)号：US20220327362A1

公开(公告)日：2022-10-13

申请号：US17850335

申请日：2022-06-27

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Tomoyuki OKUNO ,  Yohei NAKATA ,  Yasunori ISHII

IPC: G06N3/04 ,  G06N3/08

Abstract: First data is input to a first model to obtain a first result, the first data is input to a second model to obtain a second result, an error between discriminating information about the first result input to a discriminating model and correct answer information indicating an output of the first model is obtained, an error between discriminating information about the second result input to the discriminating model and correct answer information indicating an output of the second model is obtained, the discriminating model is trained by machine learning to reduce the errors, second data is input to the second model to obtain a third result, an error between discriminating information about the third result input to the discriminating model and correct answer information indicating an output of the first model is obtained, and the second model is trained by machine learning to reduce the error.

公开(公告)号：US20210374541A1

公开(公告)日：2021-12-02

申请号：US17404312

申请日：2021-08-17

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Yasunori ISHII

IPC: G06N3/08 ,  G06N3/04

Abstract: In an information processing method to be executed by a computer, with a first model trained through machine learning to output data simulating noise-reduced data in response to input noise-containing data, feature data of first data generated by the first model generated via processes leading up to output of second data simulating noise-reduced first data of input noise-containing first data is obtained; this feature data is input to a second model that is an estimation model, and inference result data that the second model outputs in response to an input of the feature data is obtained; and the second model is trained through machine learning based on the inference result data and reference data that is for making inference about the first data.

公开(公告)号：US20200082197A1

公开(公告)日：2020-03-12

申请号：US16558960

申请日：2019-09-03

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Stefano ALLETTO ,  Sotaro TSUKIZAWA ,  Yasunori ISHII

IPC: G06K9/40 ,  G06K9/62 ,  G06K9/68

Abstract: An information processing method includes: obtaining noise region estimation information output from a first converter by a first image including a noise region being input to the first converter; obtaining a second image, on which noise region removal processing has been performed, output from a second converter by the noise region estimation information and the first image being input to the second converter; generating a fourth image including the estimated noise region by using the noise region estimation information and a third image including no noise region and a scene corresponding to the first image; training the first converter by using machine learning in which the first image is reference data and the fourth image is conversion data; and training the second converter by using machine learning in which the third image is reference data and the second image is conversion data.

公开(公告)号：US20200074231A1

公开(公告)日：2020-03-05

申请号：US16543022

申请日：2019-08-16

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Yasunori ISHII ,  Hiroaki URABE

IPC: G06K9/62 ,  G06N20/00

Abstract: An information processing method includes: obtaining sensing data; determining a synthesis region in the sensing data in which recognition target data is to be synthesized with the sensing data; generating composite data by synthesizing the recognition target data into the synthesis region, the recognition target data having same or similar characteristics perceived by a human sensory system as the sensing data; obtaining recognition result data by providing the composite data to a model which has been trained using machine learning to recognize a recognition target; making a second determination based on the recognition result data and reference data including at least the synthesis region, the second determination being to determine whether to make a first determination, the first determination being to determine training data for the model based on the composite data; and making the first determination when it is determined in the second determination to make the first determination.

公开(公告)号：US20190236463A1

公开(公告)日：2019-08-01

申请号：US16256335

申请日：2019-01-24

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Yohei NAKATA ,  Sotaro TSUKIZAWA ,  Yasunori ISHII

IPC: G06N5/04 ,  G06N3/04 ,  G06K9/00 ,  G06N3/08 ,  G06N20/00

CPC classification number: G06N5/04 ,  G06K9/00536 ,  G06N3/0454 ,  G06N3/063 ,  G06N3/08 ,  G06N3/084 ,  G06N20/00

Abstract: In a data processing method executed by a computer: inputting, in a third trained model, first output data corresponding to first input data for a first trained model to obtain second output data, the third trained model being acquired through training in which (i) output data of the first trained model is used as training data, and (ii) output data of a second trained model acquired by converting the first trained model is used as label data; obtaining first label data of the first input data; and retraining the first trained model using first differential data corresponding to differences between the second output data and the first label data.