US Patent Issued to ROBERT BOSCH on Sept. 30 for "Training method for a generator neural network imposing data equivariances" (German, Dutch Inventors)

ALEXANDRIA, Va., Sept. 30 -- United States Patent no. 12,430,550, issued on Sept. 30, was assigned to ROBERT BOSCH GMBH (Stuttgart, Germany).

"Training method for a generator neural network imposing data equivariances" was invented by Anna Khoreva (Stuttgart, Germany), Dan Zhang (Leonberg, Germany) and Edgar Schoenfeld (Amsterdam).

According to the abstract* released by the U.S. Patent & Trademark Office: "A training method for training a generator neural network configured to generate synthesized sensor data. A fidelity destroying transformation is defined configured to transform a measured sensor data to obtain a fidelity-destroyed transformed measured sensor data. A fidelity preserving transformation is defined configured to transform ...