Videos

“A Practitioner’s Guide to Commercializing Applications of Computer Vision,” a Presentation from Firelake Capital Management

Edge AI and Vision Alliance, Videos /

Peter Shannon, Managing Director at Firelake Capital Management, presents the "Practitioner’s Guide to Commercializing Applications of Computer Vision" tutorial at the May 2016 Embedded Vision Summit. Computer vision technology is advancing at an exciting pace, but still has a long way to go toward maturity and realizing its full potential. The technology itself presents attractive […]

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“The OpenCV Open Source Computer Vision Library: What’s New and What’s Coming?,” a Presentation from the OpenCV Foundation

Algorithms & Models, Edge AI and Vision Alliance, Software, Tools, Videos /

Gary Bradski, President and CEO of the OpenCV Foundation, presents the "The OpenCV Open Source Computer Vision Library: What’s New and What’s Coming?" tutorial at the May 2016 Embedded Vision Summit. OpenCV is an enormously popular open source computer vision library, with over 14 million downloads expanding recently to 200K downloads per month. Originally used

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“Democratizing Computer Vision Development: Lessons from the Video Game Industry,” a Presentation from WRNCH

Edge AI and Vision Alliance, Entertainment, Software, Tools, Videos /

Paul Kruszewski, President of WRNCH, presents the "Democratizing Computer Vision Development: Lessons from the Video Game Industry" tutorial at the May 2016 Embedded Vision Summit. Computer vision offers great promise: algorithms are maturing rapidly and processing power continues to grow by leaps and bounds. But today’s approach to computer vision software development – hiring a

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“Computer Vision in Cars: Status, Challenges, and Trends,” a Presentation from videantis

Algorithms & Models, Automotive, Processors, Sensors and Cameras, videantis, Videos /

Marco Jacobs, Vice President of Marketing at videantis, presents the "Computer Vision in Cars: Status, Challenges, and Trends" tutorial at the May 2016 Embedded Vision Summit. Just as horse carriages were replaced by cars in the 1920s, human operators in our cars will be replaced by electronics in the 2020s. The benefits are tremendous: self-driving

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“Computer Vision 2.0: Where We Are and Where We’re Going,” a Presentation from the Embedded Vision Alliance

Algorithms & Models, Processors, Sensors and Cameras, Software, Tools, Videos /

Jeff Bier, founder of the Embedded Vision Alliance, presents the "Computer Vision 2.0: Where We Are and Where We're Going" plenary session at the May 2016 Embedded Vision Summit. Computer vision has rapidly transitioned from a research topic with few commercial applications to a mainstream technology with applications in virtually every sector of our economy.

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“Computational Photography: Understanding and Expanding the Capabilities of Standard Cameras,” a Presentation from NVIDIA

Algorithms & Models, NVIDIA, Processors, Sensors and Cameras, Software, Tools, Videos /

Orazio Gallo, Senior Research Scientist at NVIDIA, presents the "Computational Photography: Understanding and Expanding the Capabilities of Standard Cameras" tutorial at the May 2016 Embedded Vision Summit. Today's digital cameras, even at the entry-level, produce pictures with quality comparable to that of high-end cameras of a decade ago. Image processing and computational photography algorithms play

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“Large-Scale Deep Learning for Building Intelligent Computer Systems,” a Keynote Presentation from Google

Algorithms & Models, Edge AI and Vision Alliance, Processors, Software, Tools, Videos /

Jeff Dean, Senior Fellow at Google, presents the "Large-Scale Deep Learning for Building Intelligent Computer Systems" keynote at the May 2016 Embedded Vision Summit. Over the past few years, Google has built two generations of large-scale computer systems for training neural networks, and then applied these systems to a wide variety of research problems that

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“Techniques for Efficient Implementation of Deep Neural Networks,” a Presentation from Stanford

Algorithms & Models, Biometrics, Edge AI and Vision Alliance, Emotion Discernment, Face Recognition, Gesture Control, Object Identification, Object Tracking, Optical Character Recognition, Videos /

Song Han, graduate student at Stanford, delivers the presentation "Techniques for Efficient Implementation of Deep Neural Networks" at the March 2016 Embedded Vision Alliance Member Meeting. Song presents recent findings on techniques for the efficient implementation of deep neural networks.

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Cadence Demonstrations of a German Traffic Sign Recognition Benchmark and a Smartphone

Videos /

Dennis Crespo, Director of Product Marketing at Cadence, demonstrates the company's latest embedded vision technologies and products at the March 2016 Embedded Vision Alliance Member Meeting. Specifically, Crespo demonstrates a German traffic sign recognition benchmark running on the company's Tensilica Vision P5 DSP core, using a convolutional neural network algorithm and integrated in a Xilinx

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