{
  "$type": "site.standard.document",
  "description": "A computer-implemented method for updating a perception function of a vehicle having an Automated Driving System (ADS) is disclosed. The ADS has a machine-learning algorithm for: generating an attention map or a feature map based on one or more ingested images and for providing one or more…",
  "path": "/patents/1357626",
  "publishedAt": "2024-01-11T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "B60W60/001",
    "ZENSEACT AB"
  ],
  "textContent": "A computer-implemented method for updating a perception function of a vehicle having an Automated Driving System (ADS) is disclosed. The ADS has a machine-learning algorithm for: generating an attention map or a feature map based on one or more ingested images and for providing one or more in-vehicle perception functions based on one or more ingested images. The method comprises obtaining one or more images of a scene in a surrounding environment of the vehicle, and updating one or more model parameters of the self-supervised machine-learning algorithm in accordance with a self-supervised machine learning process based on the obtained one or more images. The method further comprises generating a first output comprising an attention map or a feature map by processing the obtained one or more images by using the self-supervised machine-learning algorithm, and generating a supervisory signal for a supervised learning process based on the first output.",
  "title": "METHOD AND SYSTEM FOR IN-VEHICLE SELF-SUPERVISED TRAINING OF PERCEPTION FUNCTIONS FOR AN AUTOMATED DRIVING SYSTEM"
}