TinyML Articles - Page 2 of 11

ESP32-TinyML: Unlocking The Power Of Embedded Micro Machine Learning!

2026-04-30 by boardor

The ESP32-TinyML project brings powerful micro machine learning capabilities to Internet of Things (IoT) devices, allowing you to run complex machine learning models on the resource-constrained ESP32 microcontroller. This article introduces the project, explores its features, usage, and potential applications. Project Overview: Running TinyML on ESP32 The ESP32-TinyML project provides a complete set of tools … Read more

TinyML Breakthrough: Sensing MCU Status Through Induced Current

2026-04-30 by boardor

Introduction: Imagine being able to decipher the internal operational status of a target device merely by monitoring its induced current, without any physical contact. This sounds like a plot from a sci-fi movie, but thanks to the rapid advancements in TinyML technology, it has become a reality! The CurrentSense-TinyML project launched by the Santander security … Read more

ESP32-TinyML: Empowering Your Micro Devices with AI

2026-04-30 by boardor

In recent years, artificial intelligence technology has developed rapidly, but its applications are often limited to large servers and high-performance devices. However, with the rise of TinyML technology, embedded devices can now possess an ‘AI brain’. The ESP32, as a cost-effective microcontroller, has become an ideal platform for TinyML. This article will introduce ESP32-TinyML in … Read more

TinyML-CAM: 80FPS Real-Time Image Recognition with 1KB Memory

2026-04-30 by boardor

In recent years, artificial intelligence (AI) technology has rapidly developed, but its high computational resource demands often limit its application scenarios. The emergence of TinyML (Tiny Machine Learning) brings hope for AI applications on edge devices. Today, we will introduce an astonishing TinyML project—TinyML-CAM, which can achieve real-time image recognition with incredible efficiency on extremely … Read more

TGTM: TinyML-based Global Tone Mapping for HDR Sensors

2026-02-12 by boardor

Paper Title TGTM: TinyML-based Global Tone Mapping for HDR Sensors 1 IntroductionAdvanced Driver Assistance Systems (ADAS) that rely on multiple cameras are becoming increasingly popular in vehicle technology.However, traditional imaging sensors struggle to capture clear images in conditions with strong lighting contrasts, such as at the exit of tunnels, due to their limited dynamic range.Introducing … Read more

Implementing Artificial Intelligence and Machine Learning on Low-Power MCUs

2026-02-09 by boardor

(Written by Silicon Labs) Artificial Intelligence (AI) and Machine Learning (ML) technologies are not only rapidly evolving but are also being innovatively applied to low-power microcontrollers (MCUs) to achieve edge AI/ML solutions. These MCUs are an essential part of many embedded systems, capable of supporting AI/ML applications due to their cost-effectiveness, high energy efficiency, and … Read more

Can Low-Power MCUs Run AI? Unveiling TinyML Application Practices!

2026-02-08 by boardor

Artificial Intelligence(AI) on edge devices is revolutionizing the field of embedded electronics by enabling advanced computing capabilities directly on low-power devices. Traditionally, neural networks required powerful hardware and abundant resources, but with the development of technologies like TinyML, inference can now be performed directly on devices even with limited computational resources. Deploying neural networks on … Read more

A New Era of Smart Living: Practical Applications of AI and Microcontroller Integration

2026-02-05 by boardor

In the field of embedded systems, microcontrollers (MCUs) serve as core control units and are widely used in home appliances, industrial control, and the Internet of Things (IoT). However, traditional microcontroller development has a high barrier to entry and relatively fixed functions, limiting its potential in the era of intelligence. With the rapid development of … Read more

TinyFormer: A 300KB Model Surpassing MobileNetv2, Achieving 50x Speedup with LayerNorm!

2026-01-26 by boardor

↑ ClickBlue text Follow the Extreme City platformAuthor丨AI Vision EngineSource丨AI Vision EngineEditor丨Extreme City Platform Extreme City Guide This article presents the TinyFormer framework for developing Transformers on resource-constrained devices. By implementing a minimal and efficient Transformer on MCUs, it introduces Transformers into the TinyML scenario. Experimental results on CIFAR-10 show that TinyFormer achieves 96.1% accuracy, … Read more

A Discussion on EdgeML (Edge Machine Learning) and TinyML (Tiny Machine Learning)

2026-01-06 by boardor

EdgeML (Edge Machine Learning) and TinyML (Tiny Machine Learning) are two important subfields that have rapidly developed in the field of artificial intelligence in recent years. They both aim to deploy machine learning models’ inference (and sometimes even training/fine-tuning) close to the data source (sensors, devices), rather than relying on cloud data centers. This brings … Read more