Interactive neural network training in adverse conditions for revoking bias in driving

A non-transitory computer readable medium for interactive neural network training for driving, the non-transitory computer readable medium stores instructions executable by a processing circuit for:

• identifying, during a first process and across a first set of images of road elements captured in an environment of a vehicle and using a neural network to output first driving related outcomes, an image comprising a combination of elements in an initial scenario that is below a confidence level threshold;
• determining the combination in the initial scenario as a bias;
• interacting, responsive to the determining, with a second set of images, using the neural network to output second driving related outcomes, wherein the second set of images are created, at least in part, artificially in correspondence with the first set of images and each comprising at least one of:
• an element of the combination of elements, or a different combination of the elements, to contain a sample combination of image samples based on the determined bias;
• and
• revoking, with the second process running interactively with the first process, the determined bias in the first process, by interacting with the first process using the second driving related outcomes of the second process.