Engineer, inventor and YouTube personality Mark Rober presents the "Adventures in DIY Embedded Vision: The Can’t-miss Dartboard" tutorial at the May 2017 Embedded Vision Summit. Can a mechanical engineer with no background in computer vision build a complex, robust, real-time computer vision system? Yes, with a little help from his friends. Rober fulfilled a three-year […]
Andrew Rabinovich, Director of Deep Learning at Magic Leap, presents the "Performing Multiple Perceptual Tasks With a Single Deep Neural Network" tutorial at the May 2017 Embedded Vision Summit. As more system developers consider incorporating visual perception into smart devices such as self-driving cars, drones and wearable computers, attention is shifting toward practical formulation and
LETTER FROM THE EDITOR Dear Colleague, TensorFlow has become a popular framework for creating machine learning-based computer vision applications, especially for the development of deep neural networks (DNNs). If you’re planning to develop computer vision applications using deep learning and want to understand how to use TensorFlow to do it, then don’t miss an upcoming
Embedded Vision Insights: August 29, 2017 Edition Read More +
Boris Babenko, Senior Software Engineer at Orbital Insight, presents the "Using Satellites to Extract Insights on the Ground" tutorial at the May 2017 Embedded Vision Summit. Satellites are great for seeing the world at scale, but analyzing petabytes of images can be extremely time-consuming for humans alone. This is why machine vision is a perfect
Chris Osterwood, Chief Technical Officer at Carnegie Robotics, presents the "How to Choose a 3D Vision Technology" tutorial at the May 2017 Embedded Vision Summit. Designers of autonomous vehicles, robots, and many other systems are faced with a critical challenge: Which 3D perception technology to use? There are a wide variety of sensors on the
“How to Choose a 3D Vision Technology,” a Presentation from Carnegie Robotics Read More +
Mark Bünger, VP of Research at Lux Research, presents the "Automakers at a Crossroads: How Embedded Vision and Autonomy Will Reshape the Industry" tutorial at the May 2017 Embedded Vision Summit. The auto and telecom industries have been dreaming of connected cars for twenty years, but their results have been mediocre and mixed. Now, just
LETTER FROM THE EDITOR Dear Colleague, TensorFlow has become a popular framework for creating machine learning-based computer vision applications, especially for the development of deep neural networks. If you’re planning to develop computer vision applications using deep learning and want to understand how to use TensorFlow to do it, then don’t miss an upcoming full-day,
Embedded Vision Insights: August 18, 2017 Edition Read More +
Jessica Gehlhar, Vision Solutions Engineer at Edmund Optics, presents the “Introduction to Optics for Embedded Vision” tutorial at the May 2017 Embedded Vision Summit. This talk provides an introduction to optics for embedded vision system and algorithm developers. Gehlhar begins by presenting fundamental imaging lens specifications and quality metrics. She explains key parameters and concepts
“Introduction to Optics for Embedded Vision,” a Presentation from Edmund Optics Read More +
Rudy Burger, Managing Partner at Woodside Capital Partners, presents the "What’s Hot? The M&A and Funding Landscape for Computer Vision Companies" tutorial at the May 2017 Embedded Vision Summit. The six primary markets driving computer vision are automotive, sports and entertainment, consumer and mobile, robotics and machine vision, medical, and security and surveillance. This presentation
Jay Yagnik, Head of Machine Perception Research at Google, presents the "Rapid Evolution and Future of Machine Perception" tutorial at the May 2017 Embedded Vision Summit. With the advent of deep learning, our ability to build systems that derive insights from perceptual data has increased dramatically. Perceptual data dwarfs almost all other data sources in
“The Rapid Evolution and Future of Machine Perception,” a Presentation from Google Read More +
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