Abstract
A system is disclosed that includes a computer that includes a processor and a memory, the memory including instructions executable by the processor to input an image acquired by a sensor to a neural network to output a prediction regarding an object included in the image. The neural network can be trained, based on (a) a distributed robust optimization that minimizes an expectation applied to probability distributions of loss functions to select training images that yield a solution with a selected uncertainty level and (b) generating additional input images based on adversarial images.
Inventors
Xinru Hua, Huanzhong Xu, Jose Blanchet, Viet Anh Nguyen, Marcos Paul Gerardo Castro
Publication date
2024/5/2
Patent office
US
Application number
18051578
