32 citations · 49 across the 7 of their papers we have counts for
8 papers
Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles
Yu-Shun Hsiao, Siva Kumar Sastry Hari, Michał Filipiuk +5
The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading saf…
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio +5
Extracting interesting scenarios from real-world data as well as generating failure cases is important for the development and testing of autonomous systems. We propose efficient m…
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Kumar Sastry Hari, Michael B. Sullivan, Timothy Tsai +1
The ability of Convolutional Neural Networks (CNNs) to accurately process real-time telemetry has boosted their use in safety-critical and high-performance computing systems. As su…
Estimating Silent Data Corruption Rates Using a Two-Level Model
Siva Kumar Sastry Hari, Paolo Rech, Timothy Tsai +7
High-performance and safety-critical system architects must accurately evaluate the application-level silent data corruption (SDC) rates of processors to soft errors. Such an evalu…
ML-driven Malware that Targets AV Safety
Saurabh Jha, Shengkun Cui, Subho S. Banerjee +3
Ensuring the safety of autonomous vehicles (AVs) is critical for their mass deployment and public adoption. However, security attacks that violate safety constraints and cause acci…
HarDNN: Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher +7
As Convolutional Neural Networks (CNNs) are increasingly being employed in safety-critical applications, it is important that they behave reliably in the face of hardware errors. T…