Assessment of Machine Learning Algorithms for Near-Sensor Computing under Radiation Soft Errors-Reference-Cited by-同舟云学术

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Assessment of Machine Learning Algorithms for Near-Sensor Computing under Radiation Soft Errors

Published:2020-11-23 Issue: Volume: Page:
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Container-title:2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)
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Author:

Trindade M. Garay,Bastos R. Possamai,Garibotti R.,Ost L.,Letiche M.,Beaucour J.

Funder

IRT Nanoelec

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9294155/9294779/09294938.pdf?arnumber=9294938

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessment of Radiation-Induced Soft Error on Unmanned Surface Vehicles;IEEE Transactions on Nuclear Science;2024-08

2. DeBaTE-FI: A Debugger-Based Fault Injector Infrastructure for IoT Soft Error Reliability Assessment;2023 IEEE 9th World Forum on Internet of Things (WF-IoT);2023-10-12

3. Supervised Deep Learning and Classification of Single-Event Transients;IEEE Transactions on Nuclear Science;2023-08

4. A Lightweight Mitigation Technique for Resource- Constrained Devices Executing DNN Inference Models Under Neutron Radiation;IEEE Transactions on Nuclear Science;2023-08

5. Power, Performance and Reliability Evaluation of Multi-thread Machine Learning Inference Models Executing in Multicore Edge Devices;2023 IEEE Computer Society Annual Symposium on VLSI (ISVLSI);2023-06-20

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