Accelerating End-to-End Automated Accuracy Evaluation of Deep Neural Networks Under Hardware Transient Faults
Abstract: Hardware transient faults have been shown to significantly impact deep neural networks, especially in safety-critical applications such as autonomous vehicles, healthcare, and aerospace, where the probability of misclassification can increase by up to four times. However, accurately assessing inaccuracies using precise fault injection methods is very time-consuming, potentially requiring several hours or even days … Read more