This blog post was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. The development of vision algorithms, software and systems is very much an empirical undertaking – informed more my experimentation and experience than by theory. The good news is, you don’t have to do all of […]
Gerrit Fischer, Head of Product Market Management at Basler, presents the "Understanding Camera Subsystems for Your Embedded Vision System and Making the Right Choice" tutorial at the May 2016 Embedded Vision Summit. More than ever, you have a wide range of camera subsystems to choose from. At one end of the spectrum, a system designer
This blog post was originally published at ARM's website. It is reprinted here with the permission of ARM. Welcome to the next installment of my VR blog series. In previous VR blogs we’ve considered the importance of clear focus to a VR experience, as well as the essential requirement to keep ‘motions to photons’ latency
New 8-megapixel device is first with improved near-infrared sensitivity for machine vision and other applications. PHOENIX, AZ – July 11, 2016 – ON Semiconductor (Nasdaq: ON), driving energy efficient innovations, is enhancing imaging performance in demanding industrial applications with technology that improves the near-infrared sensitivity of CCD image sensors. The 8 megapixel (MP) KAI-08052 image
ON Semiconductor Enhances Near-Infrared Performance of CCD Image Sensors Read More +
Paul Brasnett, Principal Research Engineer at Imagination Technologies, presents the "Efficient Convolutional Neural Network Inference on Mobile GPUs" tutorial at the May 2016 Embedded Vision Summit. GPUs have become established as a key tool for training of deep learning algorithms. Deploying those algorithms on end devices is a key enabler to their commercial success and
Bill Jenkins, Senior Product Specialist for High Level Design Tools at Intel, presents the "Accelerating Deep Learning Using Altera FPGAs" tutorial at the May 2016 Embedded Vision Summit. While large strides have recently been made in the development of high-performance systems for neural networks based on multi-core technology, significant challenges in power, cost and, performance
“Accelerating Deep Learning Using Altera FPGAs,” a Presentation from Intel Read More +
On July 27 at 1PM ET (10AM PT), CEVA will give a free hour-long webinar entitled "Deep Learning on Embedded Systems". Here's the description, from the event page: As Artificial Intelligence (AI) marches into almost every aspects of our lives, one of the major challenges is bringing this intelligence to small, low-power devices. This requires
“Deep Learning on Embedded Systems”: A Free Webinar from CEVA Read More +
This blog post was originally published at Vision Systems Design's website. It is reprinted here with the permission of PennWell. Convolutional neural networks (CNNs) and other deep learning techniques are rapidly becoming key enabling technologies for applications requiring object recognition and other computer vision capabilities. I first discussed the topic of deep learning in a
FEATURED VIDEOS "Challenges in Object Detection on Embedded Devices," a Presentation from CEVA As more products ship with integrated cameras, says Adar Paz, Imaging and Computer Vision Team Leader at CEVA, there is an increased potential for computer vision (CV) to enable innovation. For instance, CV can tackle the "scene understanding" problem by first figuring
Embedded Vision Insights: July 7, 2016 Edition Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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