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

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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 […]

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“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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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

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May 2017 Embedded Vision Summit Vision Tank Competition Finalist Presentations

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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

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“OpenCV on Zynq: Accelerating 4k60 Dense Optical Flow and Stereo Vision,” a Presentation from Xilinx

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Nick Ni, Senior Product Manager for SDSoC and Embedded Vision at Xilinx, presents the "OpenCV on Zynq: Accelerating 4k60 Dense Optical Flow and Stereo Vision" tutorial at the May 2017 Embedded Vision Summit. OpenCV libraries are widely used for algorithm prototyping by many leading technology companies and computer vision researchers. FPGAs can achieve unparalleled compute

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May 2017 Embedded Vision Summit Vision Entrepreneurs’ Panel

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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

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“Techniques to Reduce Power Consumption in Embedded DNN Implementations,” a Presentation from Cadence

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Samer Hijazi, Deep Learning Engineering Group Director at Cadence, presents the "Techniques to Reduce Power Consumption in Embedded DNN Implementations" tutorial at the May 2017 Embedded Vision Summit. Deep learning is becoming the most widely used technique for computer vision and pattern recognition. This rapid adoption is primarily driven by the outstanding effectiveness deep learning

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“The Power of a Turnkey Camera Solution: Introduction to the Camera Development Kit”, a Presentation from Thundersoft

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Fan Wang, Technical Director at Thundersoft, presents the "Power of a Turnkey Camera Solution: Introduction to the Camera Development Kit" tutorial at the May 2017 Embedded Vision Summit. In this presentation, Wang showcases the power of a turn-key camera solution via the company's camera development kit, which can be used for algorithm development and smart

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“Fast Inference in Low Power Systems via CEVA’s Deep Neural Network Solution,” a Presentation from CEVA

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Yair Siegel, Director of Strategic Marketing at CEVA, presents the "Fast Inference in Low Power Systems via CEVA’s Deep Neural Network Solution" tutorial at the May 2017 Embedded Vision Summit. The emergence of state-of-the-art, real-time object detection solely based on convolutional neural networks has created new and complex challenges for embedded systems. Algorithms such as

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“Scalable Neural Network Processors for Embedded Applications,” a Presentation from Cadence

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Pulin Desai, Director of Product Marketing at Cadence, presents the "Scalable Neural Network Processors for Embedded Applications" tutorial at the May 2017 Embedded Vision Summit. This presentation describes the architecture of the latest Tensilica-based neural network processor IP and illustrates how easily different neural networks can be run using it. See how this low-power architecture

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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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