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Found 3 papers, 1 papers with code
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators
As Deep Neural Networks (DNNs) are increasingly deployed in safety critical and privacy sensitive applications such as autonomous driving and biometric authentication, it is critical to understand the fault-tolerance nature of DNNs.
Eudoxus: Characterizing and Accelerating Localization in Autonomous Machines
We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe.
Self-Driving Cars
Hardware Architecture
TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids
Modern speech enhancement algorithms achieve remarkable noise suppression by means of large recurrent neural networks (RNNs).
