AUTOMATIC REMOVAL OF SELECTED TRAINING DATA FROM DATASET

Organization Name

Inventor(s)

[[:Category:Sven M�ller of Lubbecke (DE)|Sven M�ller of Lubbecke (DE)]][[Category:Sven M�ller of Lubbecke (DE)]]

AUTOMATIC REMOVAL OF SELECTED TRAINING DATA FROM DATASET

This abstract first appeared for US patent application 20250077958 titled 'AUTOMATIC REMOVAL OF SELECTED TRAINING DATA FROM DATASET

Original Abstract Submitted

autonomous vehicles utilize perception to identify objects in a vehicle's surrounding environment and plan a trajectory. in perceiving an av's surroundings, an object detection model uses sensor data from av sensors to detect objects in the av surroundings. an object detection model can be trained to detect objects using training datasets having sensor data and ground truth objects. in training, the object detection model uses the sensor data to identify objects in the locations of the ground truth objects. however, sometimes there is little or no sensor data corresponding to the ground truth objects, and the model is not able to learn patterns in sensor data to correctly detect the objects. systems and methods are provided herein for removing ground truth objects that do not have sufficient corresponding sensor data from the training dataset, thereby preventing these objects from dominating the loss and interfering with the model learning useful patterns.