Benchmarking In-Sensor Machine Learning Computing: An Extension to the MLCommons-Tiny Suite
This paper proposes a new benchmark specifically designed for in-sensor digital machine learning computing to meet an ultra-low embedded memory requirement. With the exponential growth of edge devices, efficient local processing is essential to mitigate economic costs, latency, and privacy concerns...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
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| Series: | Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/15/11/674 |
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