Browsing Data Science Institute (Conference Papers) by Subject "Offline Inference"
Now showing items 1-3 of 3
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An SRAM optimized approach for constant memory consumption and ultra-fast execution of ML classifiers on TinyML hardware
(Institute of Electrical and Electronics Engineers, 2021-11-15)With the introduction of ultra-low-power machine learning (TinyML), IoT devices are becoming smarter as they are driven by Machine Learning (ML) models. However, any increase in the training data results in a linear ... -
TinyML benchmark: Executing fully connected neural networks on commodity microcontrollers
(National University of Ireland Galway, 2021-06-20)Recent advancements in the field of ultra-low-power machine learning (TinyML) promises to unlock an entirely new class of edge applications. However, continued progress is restrained by the lack of benchmarking Machine ... -
Ultra-fast machine learning classifier execution on IoT devices without SRAM consumption
(Institute of Electrical and Electronics Engineers (IEEE), 2021-05-25)With the introduction of edge analytics, IoT devices are becoming smart and ready for AI applications. A few modern ML frameworks are focusing on the generation of small-size ML models (often in kBs) that can directly be ...