公开(公告)号：US12175734B2

公开(公告)日：2024-12-24

申请号：US16969072

申请日：2019-02-11

Applicant: RENSSELAER POLYTECHNIC INSTITUTE

Inventor： Ge Wang ,  Daniel David Harrison ,  Xun Jia ,  Klaus Mueller

IPC: G01N33/48 ,  A61B5/00 ,  G06F18/214 ,  G06N3/04 ,  G06N3/08 ,  G06N3/10 ,  G06N20/00 ,  G06T11/00 ,  G06V10/82

Abstract: In some embodiments, a method of machine learning includes identifying, by an auto encoder network, a simulator feature based, at least in part, on a received first simulator data set and an emulator feature based, at least in part, on a received first emulator data set. The method further includes determining, by a synthesis control circuitry, a synthesized feature based, at least in part, on the simulator feature and based, at least in part, on the emulator feature; and generating, by the auto encoder network, an intermediate data set based, at least in part, on a second simulator data set and including the synthesized feature. Some embodiments of the method further include determining, by a generative artificial neural network, a synthesized data set based, at least in part, on the intermediate data set and based, at least in part, on an objective function.

公开(公告)号：US20210035340A1

公开(公告)日：2021-02-04

申请号：US16969072

申请日：2019-02-11

Applicant: RENSSELAER POLYTECHNIC INSTITUTE

Inventor： Ge Wang ,  Daniel David Harrison ,  Xun Jia ,  Klaus Mueller

IPC: G06T11/00 ,  G06N3/04 ,  G06N3/08 ,  G06K9/62

Abstract: In some embodiments, a method of machine learning includes identifying, by an auto encoder network, a simulator feature based, at least in part, on a received first simulator data set and an emulator feature based, at least in part, on a received first emulator data set. The method further includes determining, by a synthesis control circuitry, a synthesized feature based, at least in part, on the simulator feature and based, at least in part, on the emulator feature; and generating, by the auto encoder network, an intermediate data set based, at least in part, on a second simulator data set and including the synthesized feature. Some embodiments of the method further include determining, by a generative artificial neural network, a synthesized data set based, at least in part, on the intermediate data set and based, at least in part, on an objective function.