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Safety Score: A Quantitative Approach to Guiding Safety-Aware Autonomous Vehicle Computing System Design.

, , , , , , and . IV, page 1479-1485. IEEE, (2020)

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Towards Safety-Aware Computing System Design in Autonomous Vehicles., , , , , , and . CoRR, (2019)Vehicular and Edge Computing for Emerging Connected and Autonomous Vehicle Applications., , , , and . DAC, page 1-6. IEEE, (2020)Exploiting bit-depth scaling for quality-scalable energy efficient display processing., , , and . ISCAS, page 2357-2360. IEEE, (2015)Approximate image storage with multi-level cell STT-MRAM main memory., , , and . ICCAD, page 268-275. IEEE, (2017)Driving Scenario Perception-Aware Computing System Design in Autonomous Vehicles., , , , , , and . ICCD, page 88-95. IEEE, (2020)Processing-in-Memory for Energy-Efficient Neural Network Training: A Heterogeneous Approach., , , , and . MICRO, page 655-668. IEEE Computer Society, (2018)Suraksha: A Framework to Analyze the Safety Implications of Perception Design Choices in AVs., , , , , and . ISSRE, page 434-445. IEEE, (2021)Suraksha: A Quantitative AV Safety Evaluation Framework to Analyze Safety Implications of Perception Design Choices., , , , , and . DSN Workshops, page 35-38. IEEE, (2021)Safety Score: A Quantitative Approach to Guiding Safety-Aware Autonomous Vehicle Computing System Design., , , , , , and . IV, page 1479-1485. IEEE, (2020)Exploring the use of volatile STT-RAM for energy efficient video processing., , , , and . ISQED, page 81-87. IEEE, (2016)