公开(公告)号：US20200082508A1

公开(公告)日：2020-03-12

申请号：US16558908

申请日：2019-09-03

Applicant: Panasonic Intellectual Property Corporation of America

Inventor： Stefano ALLETTO ,  Luca RIGAZIO ,  Sotaro TSUKIZAWA ,  Yasunori ISHII

IPC: G06T5/00 ,  G06T5/50 ,  G06N3/08 ,  G06N20/00

Abstract: An information processing method performed using a computer includes: obtaining first sensor data (SD) that is SD of a scene and includes noise; inputting the first SD to a single converter, and obtaining second SD outputted from the single converter as a result of denoising performed on the first SD by the single converter; obtaining third SD that is SD of a scene identical or corresponding to the scene, does not include the noise, and is different from the second SD; obtaining feature information of the second SD and feature information of the third SD, based on the second SD and the third SD, respectively; and training the single converter by machine learning using the second SD and the feature information of the second SD as converted data, and using the third SD and the feature information of the third SD as reference data corresponding to the converted 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.