Advanced Search
    Li Shuangfeng. TensorFlow Lite: On-Device Machine Learning Framework[J]. Journal of Computer Research and Development, 2020, 57(9): 1839-1853. DOI: 10.7544/issn1000-1239.2020.20200291
    Citation: Li Shuangfeng. TensorFlow Lite: On-Device Machine Learning Framework[J]. Journal of Computer Research and Development, 2020, 57(9): 1839-1853. DOI: 10.7544/issn1000-1239.2020.20200291

    TensorFlow Lite: On-Device Machine Learning Framework

    • TensorFlow Lite (TFLite) is a lightweight, fast and cross-platform open source machine learning framework specifically designed for mobile and IoT. It’s part of TensorFlow and supports multiple platforms such as Android, iOS, embedded Linux, and MCU etc. It greatly reduces the barrier for developers, accelerates the development of on-device machine learning (ODML), and makes ML run everywhere. This article introduces the trend, challenges and typical applications of ODML; the origin and system architecture of TFLite; best practices and tool chains suitable for ML beginners; and the roadmap of TFLite.
    • loading

    Catalog

      Turn off MathJax
      Article Contents

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return