Machine Learning for Microcontroller-Class Hardware: A Review

@article{Saha2022MachineLF,
  title={Machine Learning for Microcontroller-Class Hardware: A Review},
  author={Swapnil Sayan Saha and Sandeep Singh Sandha and Mani B. Srivastava},
  journal={IEEE Sensors Journal},
  year={2022},
  volume={22},
  pages={21362-21390}
}
The advancements in machine learning (ML) opened a new opportunity to bring intelligence to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML deployment has high memory and computes footprint hindering their direct deployment on ultraresource-constrained microcontrollers. This article highlights the unique requirements of enabling onboard ML for microcontroller-class devices. Researchers use a specialized model development workflow for resource-limited… 
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4 Citations

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Specially-Designed Out-of-Order Processor Architecture for Microcontrollers

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E-prop on SpiNNaker 2: Exploring online learning in spiking RNNs on neuromorphic hardware

The biologically-inspired E-prop approach for training Spiking Recurrent Neural Networks (SRNNs) is implemented on a prototype of the SpiNNaker 2 neuromorphic system and is significantly more memory-efficient than other spiking neural networks.

Comparison and Evaluation of Machine Learning-Based Classification of Hand Gestures Captured by Inertial Sensors

A comparison of eight different machine learning (ML) classifiers in the task of human hand gesture recognition and classification leads to the conclusion that the LR is the most suitable classifier among tested for on-line applications in resource-constrained environments, due to its lower computational complexity in comparison with other tested algorithms.

Optimization of the 24-Bit Fixed-Point Format for the Laplacian Source

The 24-bit fixed-point format is optimized by optimization of its key parameter and by proposing two adaptation procedures, with the aim to obtain the same performance as of the optimal uniform quantizer in a wide range of variance of input data.

High-availability displacement sensing with multi-channel self mixing interferometry

: Laser self-mixing is in principle a simple and robust general purpose interferometric method, with the additional expressivity which results from nonlinearity. However, it is rather sensitive to…

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