Managing Timing Uncertainties in Worst-Case Design of Machine Learning Applications
Achieving reliable worst-case timing poses a challenge for modern, high-performance, commercial off-the-shelf hardware platforms deployed for industrial applications. Particularly for safety-critical industrial systems, e.g., robot-human collaboration using convolutional neural networks, timing must...
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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/11091311/ |
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