Retraining neural network model based on sensor data filtered for corner case

A computer-implemented method comprising:

• receiving sensor data collected during operation of a vehicle, the sensor data including images from at least one camera on the vehicle and other sensor data from at least one other sensor on the vehicle;
• identifying, based on the sensor data, a corner case for a first neural network model of an advanced driver assistance system (ADAS) of the vehicle, the corner case being identified based on being a feature or phenomenon that the first neural network model will encounter only less often than about 5% of the time in training data provided to the first neural network model;
• filtering the images to identify a subset of the images depicting the corner case, the filtering performed using a second neural network model;
• labeling the subset of the images with regard to the corner case, wherein a remainder of the images are not labeled;
• and
• retraining the first neural network model using the labeled subset of the images and a subset of the other sensor data corresponding to the subset of the images.