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Edge AI and Vision Alliance

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Object Identification, Object Tracking, Optical Character Recognition, Processors, Sensors, Software, Tools, Videos /

Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the "Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles" tutorial at the May 2017 Embedded Vision Summit. A diverse set of sensor technologies is available and emerging to provide vehicle autonomy or driver assistance. These sensor technologies often […]

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors Read More +

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Object Identification, Object Tracking, Optical Character Recognition, Processors, Sensors, Software, Tools, Videos /

Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the "Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles" tutorial at the May 2017 Embedded Vision Summit. A diverse set of sensor technologies is available and emerging to provide vehicle autonomy or driver assistance. These sensor technologies often

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors Read More +

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Building Mobile Apps with TensorFlow: An Interview with Google’s Pete Warden

Articles, Edge AI and Vision Alliance, Technical Articles /

Pete Warden, Google Research Engineer and technical lead on the company's mobile/embedded TensorFlow team, is a long-time advocate of the Embedded Vision Alliance. Warden has delivered presentations at both the 2016 ("TensorFlow: Enabling Mobile and Embedded Machine Intelligence") and 2017 ("Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP") Embedded Vision Summits, along with

Building Mobile Apps with TensorFlow: An Interview with Google’s Pete Warden Read More +

“Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP,” a Presentation from Google

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

Pete Warden, Research Engineer at Google, presents the "Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP" tutorial at the May 2017 Embedded Vision Summit. TensorFlow is Google’s second-generation deep learning software framework. TensorFlow was designed from the ground up to enable efficient implementation of deep learning algorithms at different scales, from high-performance data

“Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP,” a Presentation from Google Read More +

“Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP,” a Presentation from Google

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

Pete Warden, Research Engineer at Google, presents the "Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP" tutorial at the May 2017 Embedded Vision Summit. TensorFlow is Google’s second-generation deep learning software framework. TensorFlow was designed from the ground up to enable efficient implementation of deep learning algorithms at different scales, from high-performance data

“Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP,” a Presentation from Google Read More +

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Embedded Vision Insights: July 18, 2017 Edition

Edge AI and Vision Alliance, Newsletters /

DEEP LEARNING FOR VISION Software Frameworks and Toolsets for Deep Learning-based Vision Processing Deep learning is an increasingly popular and robust alternative to classical computer vision algorithms. This technical article from the Embedded Vision Alliance and member companies Au-Zone Technologies, BDTI, MVTec, Synopsys and Xilinx covers the leading deep learning software frameworks, the reasons for

Embedded Vision Insights: July 18, 2017 Edition Read More +

EVA180x100

Embedded Vision Insights: July 18, 2017 Edition

Edge AI and Vision Alliance, Newsletters /

DEEP LEARNING FOR VISION Software Frameworks and Toolsets for Deep Learning-based Vision Processing Deep learning is an increasingly popular and robust alternative to classical computer vision algorithms. This technical article from the Embedded Vision Alliance and member companies Au-Zone Technologies, BDTI, MVTec, Synopsys and Xilinx covers the leading deep learning software frameworks, the reasons for

Embedded Vision Insights: July 18, 2017 Edition Read More +

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Software Frameworks and Toolsets for Deep Learning-based Vision Processing

Algorithms, AMD, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, MVTec, Processors, Software, Synopsys, Technical Articles, Tools /

This article provides both background and implementation-detailed information on software frameworks and toolsets for deep learning-based vision processing, an increasingly popular and robust alternative to classical computer vision algorithms. It covers the leading available software framework options, the root reasons for their abundance, and guidelines for selecting an optimal approach among the candidates for a

Software Frameworks and Toolsets for Deep Learning-based Vision Processing Read More +

May 2017 Embedded Vision Summit Vision Tank Competition Finalist Presentations

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

Adam Rowell, CTO of Lucid VR, Nitsa Einan, VP of Business Development at Imagry, Anthony Ashbrook, Founder and CEO of Machines With Vision, Grace Tsai, Founding Engineer at PerceptIn, and Grégoire Gentil, Founder of Always Innovating, deliver their Vision Tank finalist presentations at the May 2017 Embedded Vision Summit. The Vision Tank, a unique spin

May 2017 Embedded Vision Summit Vision Tank Competition Finalist Presentations Read More +

May 2017 Embedded Vision Summit Vision Entrepreneurs’ Panel

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

Chris Rowen, CEO of Cognite Ventures, moderates the Vision Entrepreneurs' Panel at the May 2017 Embedded Vision Summit. Other panelists include Mark Bowles, founder of ecoATM; Michael Tusch, CEO; and Remi El-Ouazzane, CEO of Movidius (an Intel company). What can we learn from leaders of successful vision-based start-ups? The expanding applications of embedded vision are

May 2017 Embedded Vision Summit Vision Entrepreneurs’ Panel 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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