Self-Supervised Pretraining and Quantization for Fault Tolerant Neural Networks: Friend or Foe?
Deep neural networks (DNNs) are increasingly being applied in critical domains such as healthcare and autonomous driving. However, their predictive capabilities can degrade in the presence of transient hardware faults, which can lead to potentially catastrophic and unpredictable errors. Consequently...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10978040/ |
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