Machine vision and embedded vision systems both fulfill important roles in industry, especially in process control and automation. The difference between the two lies primarily in image processing ...

Michaël Uyttersprot, of Avnet Silica, discusses embedded vision and what is required to bring a system to market for real-world applications. Visual input is arguably the richest source of sensor ...

We use the term “embedded vision” to refer to the use of computer vision technology in embedded systems. Stated another way, “embedded vision” refers to embedded systems that extract meaning from ...

Embedded Vision and Inferencing are two critical technologies for many modern devices such as drones, autonomous cars, industrial robots, etc. Embedded vision uses computer vision to process images, ...

Presented as a virtual event, the Embedded Vision Summit will examine the latest developments in practical computer vision and edge AI processing. In my role as the summit’s general chair, I reviewed ...

Deep learning techniques such as convolutional neural networks (CNN) have significantly increased the accuracy—and therefore the adoption rate—of embedded vision for embedded systems. Starting with ...

DALLAS & FORT WORTH, Texas--(BUSINESS WIRE)--Mouser Electronics, Inc., the New Product Introduction (NPI) leader™ empowering innovation, invites design engineers to visit its exhibit at Embedded ...

The Xilinx Kria K26 targets AO vision applications in smart cities and smart factories. The first product in the company’s new portfolio of SOMs is the Kria K26 SOM, specifically targeting vision AI ...

Machine vision, a technology that until now has been largely restricted to factory production lines, is poised to enter a whole range of new applications with the development of embedded systems at ...

Solutions stack includes customizable reference designs for popular embedded vision use cases such as image sensor bridging, aggregation, splitting, and processing Includes support for new Lattice ...

Imaging technologies such as x-rays and MRI have long been critical diagnostic tools used by healthcare professionals. But it's ultimately up to a human operator to analyze and interpret the images ...