TinyML is an incredibly powerful piece of software, and you can easily train your own model and deploy it on an ESP32.
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Abstract: The evolving requirements of Internet of Things (IoT) applications are driving an increasing shift toward bringing intelligence to the edge, enabling real ...
Abstract: This paper presents PICO-TINYML-benchmark, a modular and platform-agnostic framework for benchmarking the real-time performance of TinyML models on resourceconstrained embedded systems.
Authored by embedded ML specialists with extensive experience in ESP32 voice recognition architecture, TinyML optimisation, ...
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Edge AI is here — faster, smarter, and closer to the data. In Elektor’s upcoming guest-edited edition with Edge Impulse, discover how engineers are building intelligent devices using keyword spotting, ...
这篇综述提出了一种轻量级框架,通过整合MediaPipe手部关键点检测与双分类器系统,实现了静态和动态手势的实时识别。该系统在仅使用CPU的情况下达到94.1%的准确率和30 FPS的帧率,相比CNN、Transformer和TinyML基线,在准确性、效率和可及性方面取得了更优的平衡 ...
点击下方名片,关注公众号,获取更多精彩内容 前几天小编写了2篇文章 “为什么AI会改变单片机的未来?” 单片机上如何运行AI?单片机如何“学会思考”之TinyML崛起!(含案例,建议收藏), 引起了非常多的留言、关注和加群讨论。但是,仍然有读者 ...
This comprehensive guide takes you from neural network fundamentals to building production-ready Tiny Recursive Models (TRMs) and other efficient small language models. Designed for junior ML/LLM ...