{
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  "description": "A method is provided for the efficient training of a neural network for an Automated Driving System (ADS) of a vehicle, utilizing a Central Processing Unit (CPU) to handle input/output (I/O) operations for reading and writing sensor data from a disk, and a Graphics Processing Unit (GPU) for…",
  "path": "/patents/1385560",
  "publishedAt": "2026-06-04T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G06N3/08",
    "ZENSEACT AB"
  ],
  "textContent": "A method is provided for the efficient training of a neural network for an Automated Driving System (ADS) of a vehicle, utilizing a Central Processing Unit (CPU) to handle input/output (I/O) operations for reading and writing sensor data from a disk, and a Graphics Processing Unit (GPU) for performing the network training. The method includes monitoring a GPU utilization value, which reflects the current or queued workload of the GPU, to ensure continuous, high-throughput training. If the monitored GPU utilization value is above a threshold, then the method performs the steps of reading the sensor data from the disk using the CPU, transferring it to the GPU, and training the neural network accordingly. If value is below the threshold, then the method performs the steps of generating synthetic sensor data by using the GPU, and training the neural network based on the synthetic sensor data by the GPU.",
  "title": "METHOD FOR TRAINING AN AUTOMATED DRIVING SYSTEM (ADS) OF A VEHICLE"
}