38 citations · 106 across the 12 of their papers we have counts for
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cs.AR2023★ 3 cited
To Spike or Not to Spike? A Quantitative Comparison of SNN and CNN FPGA Implementations
Patrick Plagwitz, Frank Hannig, Jürgen Teich +1
Convolutional Neural Networks (CNNs) are widely employed to solve various problems, e.g., image classification. Due to their compute- and data-intensive nature, CNN accelerators ha…
cs.LG2023★ 6 cited
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
Mark Deutel, Georgios Kontes, Christopher Mutschler +1
Deploying deep neural networks (DNNs) on microcontrollers (TinyML) is a common trend to process the increasing amount of sensor data generated at the edge, but in practice, resourc…