https://github.com/bharathsudharsan/ml-classifiers-on-mcus

Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'
https://github.com/bharathsudharsan/ml-classifiers-on-mcus

adafruit-feather arduino arm-cortex-m0 code-generation decision-tree-classifier efficient-inference esp32 microcontroller optimization random-forest-classifier stm32 tinyml

Last synced: 2 months ago
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Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'

• Host: GitHub
• URL: https://github.com/bharathsudharsan/ml-classifiers-on-mcus
• Owner: bharathsudharsan
• License: mit
• Created: 2020-11-26T17:08:13.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-07-26T12:42:15.000Z (over 3 years ago)
• Last Synced: 2023-03-03T08:48:48.181Z (almost 2 years ago)
• Topics: adafruit-feather, arduino, arm-cortex-m0, code-generation, decision-tree-classifier, efficient-inference, esp32, microcontroller, optimization, random-forest-classifier, stm32, tinyml
• Language: Jupyter Notebook
• Homepage:
• Size: 584 KB
• Stars: 12
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Porting and Execution of ML Classifiers on TinyML Hardware

**Please consider citing below paper using the BibTex entry:**

```

@inproceedings{sudharsan2021scc,

  title={An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware},

  author={Sudharsan, Bharath and Yadav, Piyush and Breslin, John G and Ali, Muhammad Intizar},

  booktitle={IEEE International Conference on Services Computing (SCC)},

  year={2021}

  }

  

```