Deep Learning on Microcontrollers: Using TinyML for Embedded AI

Deep Learning on Microcontrollers: Using TinyML for Embedded AI

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

Getting Started with TinyML: Step-by-Step Guide

Getting Started with TinyML: Step-by-Step Guide

This article is from a community submission, Author: Wang Yucheng, ML&IoT Google Developers Expert, Chief Engineer at Wenzhou University Smart Lock Research Institute.Learn more: https://blog.csdn.net/wfing In last week’s community sharing section, we introduced Getting Started with TinyML (Part 1), and this week we will continue our learning. Hello World — The Place Where Dreams Begin … Read more

Exploring the Inner Workings of Embedded Systems

Exploring the Inner Workings of Embedded Systems

The author of this article is Jean J. Labrosse, founder of Micrium and chief consultant for the Micrium product line, responsible for ensuring compliance with strict policies and standards. Jean J. Labrosse has a profound understanding of embedded systems and has authored the μC/OS series of books, which have garnered widespread attention in China! Embedded … Read more

11 Misconceptions About µC/OS

11 Misconceptions About µC/OS

↑ Click the “Mactec Technology” above to follow us On the occasion of the 25th anniversary of µC/OS, Jean Labrosse (founder of Micrium and expert in RTOS and embedded design) believes it is a good opportunity to clarify some misconceptions about this popular kernel. µC/OS, a world-renowned embedded real-time operating system (RTOS), celebrates its 25th … Read more

28 Key Points of Embedded STM32

28 Key Points of Embedded STM32

▼Click the card below to follow the public account ▼ 1. What are the differences between STM32F1 and F4? Answer: Refer to: STM32 Development – Introduction to STM32The cores are different: F1 is Cortex-M3, F4 is Cortex-M4; Different clock frequencies: F1 has a clock frequency of 72MHz, F4 has 168MHz; Floating point operations: F1 has … Read more

Understanding The Differences And Applications Of SPI, UART, And I2C Communication

Understanding The Differences And Applications Of SPI, UART, And I2C Communication

Source: Network Communication between electronic devices is like communication between humans; both parties need to speak the same language. In electronic products, these languages are called communication protocols. I previously shared articles on SPI, UART, and I2C communication separately, and this article compares them. Serial VS Parallel Electronic devices communicate by sending data bits back … Read more

Analysis of Embedded Programming vs PC Programming

Analysis of Embedded Programming vs PC Programming

In China, very few friends in embedded programming are formally graduated from computer science majors; most come from automation or electronics-related fields. These individuals have rich practical experience but lack theoretical knowledge; a large portion of those who graduated from computer science end up working on online games or web applications that are independent of … Read more

Proteus Pro 8.10 Installation and Features Overview

Proteus Pro 8.10 Installation and Features Overview

THE START Update the public account and website (search Baidu: Yuxiang Platform) for assistance with the Proteus 8.10 version. Proteus combines ease of use with powerful functionality, helping to design, test, and layout professional PCBs. The Proteus Design Suite 8 features nearly 800 variants of microcontrollers that can be simulated directly from schematics, making it … Read more

Learning TinyML From Scratch: Optimization Techniques

Learning TinyML From Scratch: Optimization Techniques

This article is contributed by the community, author Wang Yucheng, ML&IoT Google Developers Expert, Chief Engineer of the Intelligent Lock Research Institute at Wenzhou University. Learn more: https://blog.csdn.net/wfing After discussing the previous chapters, we have understood the concept of TinyML, completed the simplest TinyML model and ran it on a microcontroller, yielding the most basic … Read more

How to Implement TinyML? A Review of Efficient Neural Networks for Micro Machine Learning

How to Implement TinyML? A Review of Efficient Neural Networks for Micro Machine Learning

Tiny Machine Learning (TinyML) has gained significant attention due to its potential to enable intelligent applications on resource-constrained devices. This review provides an in-depth analysis of the advancements in efficient neural networks and the deployment methods of deep learning models for TinyML applications on ultra-low-power microcontrollers (MCUs). It first introduces neural networks along with their … Read more