★ Embedded AI Series – Analysis of YOLOv3 Model Deployment Code – Overall Process ” 1. Introduction In the previous article “Embedded AI Series – Deploying YOLOv3 Model on RV1126”, we provided the C++ source code project for deploying the YOLOv3 model in RKNN format on the RV1126 hardware platform and demonstrated the detection capabilities … Read more
In recent years, machine vision technology has rapidly developed and is widely used in various fields such as industrial automation, smart manufacturing, security monitoring, and smart retail. Traditional machine vision solutions are mostly based on X86 architecture paired with a dedicated GPU for image acquisition and AI inference processing, this “heterogeneous computing” model, while powerful, … Read more
★ Embedded AI Series – Converting YOLOv3 Model Using RKNN Toolkit ” 1 Introduction Since my development work is primarily focused on AI applications in machine vision, the commonly used model is the YOLO model. Therefore, I will demonstrate the conversion of the YOLOv3 model using the example code from the RKNN toolkit in the … Read more
★ Embedded AI Series – Installing RKNN-Toolkit (Twisted Pitfall Version) ” 1 Purpose The main purpose of installing RKNN-Toolkit is to convert existing models into the RKNN format supported by RKNPUs. As for other functionalities of RKNN-Toolkit, such as accuracy, performance, and memory usage evaluations, these are generally handled by algorithm engineers. If interested, further … Read more
[Image] Jeff Sieracki Director of Engineering, AI Center of Excellence Empowering the future of digital control, electronic commutation motors are rapidly replacing traditional designs, as these motors provide designers with unprecedented dynamic control, power, and efficiency. As engineers work in industrial, HVAC, consumer electronics…
New Breakthrough in Embedded AI: How the Replay4NCL Engine Overcomes the Challenges of Continuous Learning? -Click the blue text to follow us- Introduction In the era of booming artificial intelligence, embedded AI systems are gradually becoming the “smart brains” of various intelligent devices, from mobile robots navigating complex environments to drones soaring in the sky, … Read more
Click the blue text to follow us Every year before the Embedded Vision Summit, the author tries to reflect on the big picture of embedded AI and computer vision. This year, on the 15th anniversary of the summit, two trends are clearer than ever. First, AI and computer vision applications are moving from the laboratory … Read more
Researchers from the University of the Emirates, New York University Abu Dhabi, and the National University of Sciences and Technology in Pakistan have jointly launched an efficient memory replay method called Replay4NCL to address the challenges of continuous learning in embedded AI systems within dynamic environments. It is worth mentioning that this research has been … Read more
Embedded AI Biweekly Briefing (2017-07-24) Click the link at the end of the article to read the original text and jump to our biweekly briefing homepage, where you can read the version with item hyperlinks. Industry News OpenBLAS releases version 0.2.20 Clarifai launches SDK for training AI on your iPhone | VentureBeat We ported CAFFE … Read more
ETAS’s New Embedded AI Solutions AI modeling and code generation tools for automotive embedded systems Key ETAS tools discussed in this article: ASCMO tool family Capable of constructing AI models based on data and automatically implementing parameter optimization; Embedded AI Coder Deploys trained neural networks into high-performance embedded C code for µC and µP. Introduction … Read more