Fault detection method based on high-level feedback and reconstruction for image recognition - Xu, Jin (Nanyang Technological University, 2021)
Image recognition problem is a typical challenge for artificial intelligence. Deep learning methods have shown great progress in this area in recent years. However, this approach has the limitation of outputting wrong result with high confidence when the input is not well represented in the training data, such as adversarial examples (natural images with intentionally designed small perturbations that are imperceptible by human beings) and unusual images that is not covered in the training. This limitation causes great safety concerns for the deployment of existing deep learning systems for critical applications such as autonomous driving and medical diagnosis. However, it is not practical to include all adversarial or unusual images in training because images are highly variable.