White papers

To learn more about machine learning on Arm, see our range of available white papers: 

  • Machine Learning on Arm Cortex-M Microcontrollers

    Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing Neural Network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. CMSIS-NN is an open-source library of optimized software kernels that maximize NN performance on Cortex-M cores with minimal memory footprint overhead.

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  • Deploying Always-on Face Unlock: Integrating Face Identification, Anti-Spoofing, and Low-Power Wakeup

    Deploying Always-on Face Unlock Hero Image

    Accurate face verification has long been considered a challenge due to the number of variables, ranging from lighting to pose and facial expression. This white paper looks at a new approach – combining classic and modern machine learning (deep learning) techniques – that achieves 98.36% accuracy, running efficiently on Arm ML-optimized platforms, and addressing key security issues such as multi-user verification, as well as anti-spoofing.

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  • Packing Neural Networks into End-User Client Devices: How Number Representation Shrinks the Footprint

    Most of today’s neural networks can only run on high-performance servers. There’s a big push to change this and simplify network processing to the point where the algorithms can run on end-user client devices. One approach is to eliminate complexity by replacing floating-point representation with fixed-point representation. We take a different approach, and recommend a mix of the two, so as to reduce memory and power requirements while retaining accuracy.

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  • The Power of Speech

    Supporting Voice-Driven Commands in Small, Low-Power Microcontrollers. 
    Borrowing from an approach used for computer vision, we created a compact keyword spotting algorithm that supports voice-driven commands in edge devices that use a very small, low-power microcontroller. 

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  • The New Voice of the Embedded Intelligent Assistant

    As intelligent assistance is becoming vital in our daily lives, the technology is taking a big leap forward. Recognition Technologies and Arm have published a white paper that provides technical insight into the architecture and design approach that’s making the gateway a more powerful, efficient place for voice recognition. 

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  • Face Unlock whitepaper

    Accurate face verification has long been considered a challenge due to the number of variables, ranging from lighting to pose and facial expression.

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