To continuously improve various features in next-generation devices, wearable and hearable devices rely on memory. Memory is a key design factor for implementing advanced devices… Although wearable and hearable technologies may seem like extensions of the previous generation of handheld devices, the innovative features required to enhance their value, user experience, and functionality significantly increase … Read more
Machine Heart Report Machine Heart Editorial Team The top AI conference ICLR 2020 will be held on April 26 in Addis Ababa, Ethiopia. Among the final 2594 submitted papers, 687 were accepted, with an acceptance rate of 26.5%. This article introduces a paper accepted by the team of Zhang Quanshi from Shanghai Jiao Tong University … Read more
Editor’s note: In August this year, Lei Feng Network will hold the “Global Artificial Intelligence and Robotics Innovation Conference” (GAIR) in Shenzhen, where we will announce the “Top 25 Innovative Companies in Artificial Intelligence and Robotics”. Minieye is one of the companies we are focusing on. Today, we invite Minieye’s founder and CEO, Liu Guoqing, … Read more
TinyML, or tiny machine learning, is used to implement machine learning on resource-constrained devices such as microcontrollers and embedded systems. If you want to leverage these low-cost, low-power yet remarkably powerful devices, then this book is for you. This book aims to increase the accessibility of TinyML applications, especially for professionals who lack the resources … Read more
Part 1: Overview In this tutorial, we will develop a machine vision application using machine learning technology on the STM32H747I Discovery development board. This tutorial is officially published by STMicroelectronics. Special thanks to the Edge Intelligence Lab for the original Chinese subtitles. The documents referenced in the video (also available for download from ST’s official … Read more
Project Description This project uses the microphone built into the Syntiant TinyML development board to build a machine learning model through Edge Impulse, allowing the LED light on the board to display different effects based on Chinese voice commands. A total of four labels of sound data were trained, as detailed below. Label Keyword Action … Read more
This article is from Arduino Project Hub Author: Arduino “having11” Guy Prerequisites Like humans, plants can also get sick; for instance, the leaves of a plant may turn yellow or develop spots due to fungi or other pathogens. Thus, by harnessing the power of machine learning, we can scan the colors and then use them … Read more
Posted by: ArduinoTEAM — May 26th, 2020 Running Machine Learning (ML) on microcontrollers is one of the most exciting developments in recent years, allowing small battery-powered devices to detect complex movements, recognize sounds, or find anomalies in sensor data. To make it accessible for every embedded developer to build and deploy these models, we have … Read more
TinyML is a type of machine learning characterized by shrinking deep learning networks for use in micro hardware, primarily applied in smart devices. Ultra-low power embedded devices are “invading” our world, further promoting the proliferation of AI-driven IoT devices with the help of new embedded machine learning frameworks. FPGA has been applied across various fields … Read more
Today,the data processing architecture exhibits a “split” characteristic. The focus has shifted to “cloud” computing, which boasts massive scale and computational power, while “edge” computing places the processing right at the “front line”, connecting electronic devices with the real world. In the cloud, the volume of data stored is enormous, and processing must be queued … Read more