Join the professional CV group at Jishi, and interact with 10,000+ visual developers from prestigious institutions like HKUST, Peking University, Tsinghua University, Chinese Academy of Sciences, CMU, Tencent, Baidu, and more! We also provide monthly expert live streams, real project demand connections, valuable information summaries, and industry technical exchanges. Follow the Jishi Platform public account, … Read more
“ Nvidia launched a development board priced at only $99 at this year’s GTC – the Jetson Nano. This article will introduce how to get started with it, including the first boot, installing system packages, configuring the Python development environment, installing Keras and TensorFlow, modifying the default camera, and running classification and object detection tasks. … Read more
Exploring Python Programming for AI Chips In today’s technological era, artificial intelligence (AI) has become a hot topic. With the advancement of hardware technology, chips specifically designed for AI tasks are gradually coming into our view. These chips typically feature high performance and low power consumption, making them well-suited for applications such as deep learning … Read more
TinyML is quietly changing the landscape of industrial detection, and today we will introduce a project—tinyml-example-anomaly-detection—that not only demonstrates how to use Python to train two distinctly different machine learning models for detecting motor anomalies but also reveals the entire process from data collection to model deployment. This article will give you a comprehensive understanding … Read more
Machine Learning (ML) is a vibrant and powerful field of computer science that permeates almost all digital devices we interact with, whether it’s social media, mobile phones, cars, or even household appliances. Artificial Intelligence (AI) is rapidly moving from the “cloud” to the “edge,” entering increasingly smaller IoT devices. The machine learning processes implemented on … Read more
Learn how to deploy complex machine learning models on single-board computers, mobile phones, and microcontrollers. Main Features ● Comprehensive understanding of the core concepts of TinyML. ● Learn how to design your own TinyML applications from scratch. ● Explore cutting-edge models, hardware, and software platforms for developing TinyML. Description TinyML is an innovative technology that … Read more
Introduction This page will guide you on installing TensorFlow on a Raspberry Pi 4 running the 64-bit Bullseye operating system. TensorFlow is a large software library developed specifically for deep learning, which consumes a lot of resources. You can run TensorFlow on a Raspberry Pi 4, but do not expect miraculous performance. If the model … Read more
The Editor Says: Currently, researchers are using various deep learning frameworks. This article introduces six common deep learning frameworks and discusses the advantages of PyTorch compared to them. This article is excerpted from “Deep Learning Framework PyTorch: Introduction and Practice”. For more details, please click Read the Original. The Birth of PyTorch In January 2017, … Read more