Processors

“Deep-learning-based Visual Perception in Mobile and Embedded Devices: Opportunities and Challenges,” a Presentation from Qualcomm

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Jeff Gehlhaar, Vice President of Technology, Corporate Research and Development, at Qualcomm, presents the "Deep-learning-based Visual Perception in Mobile and Embedded Devices: Opportunities and Challenges" tutorial at the May 2015 Embedded Vision Summit. Deep learning approaches have proven extremely effective for a range of perceptual tasks, including visual perception. Incorporating deep-learning-based visual perception into devices […]

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“Combining Vision, Machine Learning and Natural Language Processing to Answer Everyday Questions,” a Presentation from QM Scientific

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Faris Alqadah, CEO and Co-Founder of QM Scientific, delivers the presentation "Combining Vision, Machine Learning and Natural Language Processing to Answer Everyday Questions" at the May 2015 Embedded Vision Alliance Member Meeting. Faris explains how his company's GPU-accelerated Quazi platform combines proprietary natural language processing, computer vision and machine learning technologies to extract, connect and

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“Understanding Adaptive Machine Learning Vision Algorithms and Implementing Them on GPUs and Heterogeneous Platforms,” a Presentation from AMD

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Harris Gasparakis, OpenCV Manager at AMD, presents the "Understanding Adaptive Machine Learning Vision Algorithms and Implementing them on GPUs and Heterogeneous Platforms" tutorial at the May 2015 Embedded Vision Summit. Machine learning algorithms are pervasive in computer vision: from object detection to object tracking to full scene recognition, generative or discriminative learning dominates the space,

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“Creating Smarter, More Interactive Apps and Systems with Computer Vision,” a Presentation from the Embedded Vision Alliance

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

Thanks to improvements in processors, image sensors, and algorithms, more and more of our devices now — for the first time — are gaining the ability to see and understand the world around them. In this talk from the June 2015 Augmented World Expo, Jeff Bier (Founder of the Embedded Vision Alliance) highlights the opportunities

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“Efficient Implementation of Convolutional Neural Networks using OpenCL on FPGAs,” a Presentation From Altera

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Deshanand Singh, Director of Software Engineering at Altera, presents the "Efficient Implementation of Convolutional Neural Networks using OpenCL on FPGAs" tutorial at the May 2015 Embedded Vision Summit. Convolutional neural networks (CNN) are becoming increasingly popular in embedded applications such as vision processing and automotive driver assistance systems. The structure of CNN systems is characterized

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“Bringing Computer Vision to the Consumer,” a Keynote Presentation from Dyson

Algorithms, Edge AI and Vision Alliance, Object Identification, Object Tracking, Processors, Robotics, Sensors and Cameras, Videos /

Mike Aldred, Electronics Lead at Dyson, presents the "Bringing Computer Vision to the Consumer" keynote at the May 2015 Embedded Vision Summit. While vision has been a research priority for decades, the results have often remained out of reach of the consumer. Huge strides have been made, but the final, and perhaps toughest, hurdle is

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“Developing High-Performance, Energy-Efficient Vision Solutions Using Open-Standard Libraries and APIs,” a Presentation from Intel

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Mostafa Hagog, Architect at Intel, presents the "Developing High-Performance, Energy-Efficient Vision Solutions Using Open-Standard Libraries and APIs" tutorial at the May 2015 Embedded Vision Summit. Connected cameras, hand-held devices, embedded systems, and cloud services enable a world of intelligence everywhere. But to realize the potential of computer vision technology, developers face tough challenges. On the

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Sorting Out Embedded Vision Systems

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This article was originally published on June 10, 2015 at Altera's website. It is reprinted here with the permission of Altera. Papers at this year’s Embedded Vision Summit suggested the vast range of ways that embedded systems can employ focused light as an input, and the even vaster range of algorithms and hardware implementations they

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“The Evolution of Object Recognition in Embedded Systems,” a Presentation from CEVA

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Moshe Shahar, Director of System Architecture at CEVA, presents the "Evolution of Object Recognition in Embedded Systems" tutorial at the May 2015 Embedded Vision Summit. Camera-enabled devices have made great strides in performance and quality in recent years, but they still fall far short of human visual perception. To reach their potential, vision-enabled systems must

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“Designing and Selecting Instruction Sets for Vision,” a Presentation From Cadence

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Chris Rowen, Fellow at Cadence, presents the "Designing and Selecting Instruction Sets for Vision" tutorial at the May 2015 Embedded Vision Summit. Two critical technical trends have reached important inflection points: the massive compute demands of vision processing and the capabilities of specialized vision processors. But what how do you actually select (or even build)

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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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