Avnet Silica has partnered with Deep Vision Consulting, an Italian AI company focused on computer vision, to launch the innovative Defect Visual Inspection (DVI) solution. This is a cost-effective, reliable, and user-friendly AI-based system designed to automate visual inspections in a variety of industries. The DVI solution is a combination of a compact system-on-module (SoM) and a software library optimised to run at the edge, making it ideal for applications in industrial, medical, food, electronics, semiconductor, packaging, and other sectors.
DVI trains the AI directly on the device and requires only a few images from samples of ‘good’ objects. The use of AI ensures a quick and easy setup process and delivers higher accuracy and fewer errors compared to either manual inspections or automatic inspections based on traditional image processing techniques, thus eliminating the need for human operators or machine learning experts. Businesses can therefore streamline their quality control processes and reduce the costs associated with traditional inspection methods.
The all-inclusive DVI product consists of a software library, system on module, camera and lens, carrier card, and more. This comprehensive package offers a cost-effective alternative to existing solutions, while maintaining a high level of performance and reliability. The system’s flexibility allows for seamless integration into various industrial applications, ensuring that companies can adapt to evolving market demands with ease.
Michael Uyttersprot, project coordinator at Avnet Silica, said, “The Defect Visual Inspection solution is a game-changer for businesses seeking to optimise their inspection processes. By harnessing the power of AI and properly optimising it to run at the edge, Avnet Silica and Deep Vision Consulting have created a stand-alone embedded system that not only offers higher accuracy and fewer errors but also simplifies the setup and integration process.”
Ryzen-based computer on module Altron Arrow
AI & ML
SolidRun announced the launch of its new Ryzen V3000 CX7 Com module, configurable with the eight-core/16-thread Ryzen Embedded V3C48 processor.
Read more...What is an NPU?
AI & ML
A neural processing unit is a specialised hardware accelerator designed to efficiently process tasks related to artificial intelligence, in particular deep learning models.
Read more...Low SWaP SoM for AI applications RFiber Solutions
AI & ML
Matchstiq’s G20 and G40 are low SWaP-C SDRs tailored for AI and ML applications by combining an RF module, SDR, FPGA, CPU, and GPU into a single transceiver platform.
Read more...Powering the intelligent edge EBV Electrolink
AI & ML
STMicroelectronics released new devices from the second generation of its industrial MPUs, the STM32MP2 series, to drive future progress in smart factories, smart healthcare, smart buildings, and smart infrastructure.
Read more...High-performance driver amplifier Avnet Silica
Telecoms, Datacoms, Wireless, IoT
The QPA0022D driver amplifier is matched to 50 O, with integrated DC blocking caps on both I/O ports for easy handling and simple system integration.
Read more...A perfect match for next-gen computing Vepac Electronics
AI & ML
Teguar’s collaboration with Hailo marks a significant step forward in their mission to provide powerful and reliable computing solutions for a wide range of industries.
Read more...High-performance low SWaP SDR RFiber Solutions
AI & ML
The Matchstiq X40 from Epiq is a high-performance low SWaP SDR optimised for AI and ML and the RF edge.
Read more...Protecting rhinos with a tech shield
AI & ML
HYDRA provides instant data creation, and aggregates data from drones, cameras, sensors, and mobile apps to provide a comprehensive picture of what’s happening across these large landscapes.
Read more...AFE enables the software-defined factory Avnet Silica
Analogue, Mixed Signal, LSI
With its software configurable analogue inputs, where each input can be configured for voltage, current, resistance, or temperature, NXP’s N-AFE enables a new level of flexibility.
printer friendly version