In this edition of Embedded Vision Insights: Recent and Upcoming Vision Events Embedded Vision Performance and Energy Optimization New Low Power Image Recognition Competition Embedded Vision in the News LETTER FROM THE EDITOR Dear Colleague, Recently, I spent three days at the Consumer Electronics Show. It was time very well spent. Many of the vision-based […]
Embedded Vision Insights: January 19, 2016 Edition Read More +
Spend any amount of time researching the topic of deep learning and you'll inevitably come across the term Caffe. This convolutional neural network (CNN) framework, originally named DeCAF, was initially developed by Yangqing Jia (now a research scientist at Google), during his Ph.D. program at the University of California, Berkeley. It is now maintained by
The Caffe Deep Learning Framework: An Interview with the Core Developers Read More +
This article was originally published at Basler's website. It is reprinted here with the permission of Basler. Ever have an inescapable need for a little something sweet? The phrase "good things come in small packages" applies not just to fine confectioneries, but also to the world of industrial machine vision. Sugarcube is a term that
Time for Something Sweet? Read More +
In this edition of Embedded Vision Insights: Embedded Vision Summit Competitions An Introduction to Computational Photography Heterogeneous Computing in Mobile Systems Embedded Vision Community Conversations Embedded Vision in the News LETTER FROM THE EDITOR Dear Colleague, Happy 2016! I hope that the holiday weeks have been relaxing and rejuvenating for you, and I wish you
Embedded Vision Insights: January 5, 2016 Edition Read More +
Neil Trevett, President of Khronos and Vice President at NVIDIA, delivers the presentation, "Update on Khronos Open Standard APIs for Vision Processing," at the December 2015 Embedded Vision Alliance Member Meeting. Trevett provides an update on recent developments in multiple Khronos standards useful for vision applications.
“An Update on Open Standard APIs for Vision Processing,” a Presentation from Khronos Read More +
In this edition of Embedded Vision Insights: Embedded Vision Summit Discount Ends Soon Real-time Hyperspectral Imaging Four Key Vision Growth Markets in 2016 Embedded Vision Community Conversations Embedded Vision in the News LETTER FROM THE EDITOR Dear Colleague, I’m pleased to announce that we’ve launched an all-new Embedded Vision Summit area of the Alliance website,
Embedded Vision Insights: December 10, 2015 Edition Read More +
Powerful vision processors have existed for some time now, as exemplified by supercomputers and the longstanding academic research on computer vision. What's recently changed are the "low-cost" and "energy-efficient" aspects of vision processing, along with evolutionary (and sometimes revolutionary) accuracy and other improvements in the algorithms running on the processors. Well-known image classification competitions like
New Competition Aims to Spur Energy-efficient Computer Vision Innovation Read More +
This article was originally published at Imagination Technologies' website, where it is one of a series of articles. It is reprinted here with the permission of Imagination Technologies. In a previous article about heterogeneous architectures, I identified memory bandwidth as the main bottleneck for implementing power-efficient algorithms for computer vision. Luckily, Imagination has created an
The PowerVR Imaging Framework for Android Read More +
This technical article was originally published at Altera's website. It is reprinted here with the permission of Altera. Deep learning neural network systems currently provide the best solution to many large computing problems for image recognition and natural language processing. Neural networks are inspired by biological systems, in particular the human brain; they use conventional
Computer vision and computational photography are intrinsic aspects of the Internet of Things (IoT), where cameras and sensors reign supreme. This article provides an overview of how computer vision technology is transforming the most critical markets in 2016: mobile, automotive, security and surveillance, and drones. Mobile The digital cameras in smartphones are one of their
How Computer Vision is Re-shaping the Four Key Growth Segments of 2016 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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