Showing 2 open source projects for "arm-aonly"

View related business solutions
  • Build Securely on Azure with Proven Frameworks Icon
    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • Earn up to 16% annual interest with Nexo. Icon
    Earn up to 16% annual interest with Nexo.

    Let your crypto work for you

    Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • 1
    Porcupine

    Porcupine

    On-device wake word detection powered by deep learning

    ...It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. Self-service. Developers can train custom wake word models using Picovoice Console. ...
    Downloads: 8 This Week
    Last Update:
    See Project
  • 2
    Apache TVM

    Apache TVM

    TVM Documentation in Chinese Simplified

    tvm-cn is a community-driven project that provides Chinese documentation for the Apache TVM deep learning compiler stack. Apache TVM is an open-source system designed to optimize and deploy machine learning models efficiently across different hardware platforms such as CPUs, GPUs, and ARM devices. The goal of the repository is to centralize translated learning materials and technical documentation so that Chinese-speaking developers can study the TVM ecosystem more easily. The project translates official TVM guides and organizes them into structured documentation that explains how to compile, optimize, and deploy deep learning models on heterogeneous hardware architectures. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next