Translation of training data between observation modalities

US11797858B2 · kind B2 · utility

Assignee

• Robert Bosch GmbH · DE

Inventors

• Gor Hakobyan · Stuttgart, DE
• Kilian Rambach · Stuttgart, DE
• Jasmin Ebert · Heidelberg, DE

Key dates

• Filing date: Sep 9, 2020
• Grant date: Oct 24, 2023
• Expiry date: Jan 4, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V30/2552
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method for training a generator. The generator is supplied with at least one actual signal that includes real or simulated physical measured data from at least one observation of the first area. The actual signal is translated by the generator into a transformed signal that represents the associated synthetic measured data in a second area. Using a cost function, an assessment is made concerning to what extent the transformed signal is consistent with one or multiple setpoint signals, at least one setpoint signal being formed from real or simulated measured data of the second physical observation modality for the situation represented by the actual signal. Trainable parameters that characterize the behavior of the generator are optimized with the objective of obtaining transformed signals that are better assessed by the cost function. A method for operating the generator, and that encompasses the complete process chain are also provided.