With the increasing prevalence of automated and assisted driving, the demand for edge computing is also on the rise. How to assist customers in developing AI applications has become a new topic. Last year, WPG introduced the eIQ edge computing solution, for more details please refer to: here. In 2020, we are introducing the new … Read more
Creative Electronic Design Training Camp Session 12 Projects Registration Instructions Hello everyone! Welcome to register for the Creative Electronic Design Training Camp – Session 12. This session offers 22 topics for groups to choose from. Please form teams based on your personal preferences. The registration channel will open shortly. Interested students can also contact the … Read more
Edge AI is increasingly being applied in embedded devices such as industrial cameras and public facility cameras, requiring embedded products to be compact and low power. The Renesas RZ/V series microprocessors (MPUs) come with a built-in AI accelerator, namely the Dynamic Reconfigurable Processor (DRP). This processor is known for its high energy efficiency, meeting the … Read more
Hello everyone, this is Juejin GitHub. With the rise of the Internet of Things and edge computing, the demand for deploying artificial intelligence (AI) applications on resource-constrained micro-devices is growing. However, traditional AI models often require a large amount of computing resources and memory, making it difficult to run on these devices. Today, we will … Read more
In the era of the Internet of Things (IoT) and edge computing, TinyML technology is becoming increasingly important. TinyML aims to deploy machine learning (ML) models on resource-constrained devices, making it possible to perform ML inference on microcontrollers. Next, we introduce TinyML-CAM, an efficient image recognition system based on the ESP32 platform. By using TinyML-CAM, … Read more
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
Tengine Tengine is a lightweight neural network inference engine developed by OPEN AI LAB, specifically optimized for Arm embedded platforms, providing excellent support for both Android and Linux systems. Moreover, what is even more valuable is that Tengine does not rely on dedicated AI chips (i.e., Tengine can utilize modules with dedicated AI acceleration capabilities … Read more
Hey, programmers, students, and tech enthusiasts! Have you ever wondered what sparks would fly if the programming giant Python met the mysterious Carson? It would be like a superhero team-up, creating a storm in the programming world! Are you eager to find out? Don’t worry, follow me, and you’ll soon get a glimpse. Python is … Read more
In today’s rapidly evolving electronic technology, printed circuit boards (PCBs) have become core components in various fields such as smart devices, automated production lines, and medical equipment. These fields have extremely high requirements for PCB quality control and production efficiency, and the precise identification of small barcodes on the boards is a key factor in … Read more
Currently, there is an increasing need for edge intelligent hardware to locally process environmental data generated in real-time by sensors and smart devices in fields such as autonomous driving, smart home systems, and industrial control, in order to minimize decision-making latency. Neuromorphic hardware, which can accurately simulate various biological neuron behaviors, is expected to drive … Read more