Invention Grant
- Patent Title: Domain generation via learned partial domain translations
-
Application No.: US16777017Application Date: 2020-01-30
-
Publication No.: US11321587B2Publication Date: 2022-05-03
- Inventor: Akhil Perincherry , Christopher Cruise
- Applicant: Ford Global Technologies, LLC
- Applicant Address: US MI Dearborn
- Assignee: Ford Global Technologies, LLC
- Current Assignee: Ford Global Technologies, LLC
- Current Assignee Address: US MI Dearborn
- Agency: Bejin Bieneman PLC
- Agent Brandon Hicks
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/00 ; G06N3/04 ; G06N3/08

Abstract:
A system and a method can receive a first dataset having a first label and a first context. The system and the method can also generate, at the trained deep neural network, a second dataset having the first label and a second context according to a mapping, wherein a first mapping of the plurality of mapping comprises one or more weights of the trained deep neural network that maps data having the first label and the first context to data having a second label and the first context and a second mapping of the plurality of mapping comprises one or more weights of the trained deep neural network that maps data having a second label and the first context to data having the second label and the second context, wherein the second context is different from the first context and the second label is different from the first label.
Public/Granted literature
- US20210241030A1 DOMAIN GENERATION VIA LEARNED PARTIAL DOMAIN TRANSLATIONS Public/Granted day:2021-08-05
Information query