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

Algorithms, Edge AI and Vision Alliance, Processors, Software, Tools, Videos / January 25, 2020

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

Algorithms, Articles, Intel, Processors, Software, Technical Articles, Tools / July 6, 2015

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

Algorithms, CEVA, Object Identification, Processors, Software, Tools, Videos / January 25, 2020

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

Algorithms, Cadence, Processors, Software, Tools, Videos / January 25, 2020

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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“Choosing a Processor for Embedded Vision: Options and Trends,” a Presentation From BDTI

Algorithms, BDTI, Processors, Software, Tools, Videos / January 25, 2020

Jeff Bier, President of Berkeley Design Technology, Inc. (BDTI) and Founder of the Embedded Vision Alliance, presents the "Choosing a Processor for Embedded Vision: Options and Trends" tutorial at the May 2015 Embedded Vision Summit. Computer vision applications typically demand lots of processor performance. These applications also tend to be complex and fast-changing, so developers …

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“Implementing Eye Tracking for Medical, Automotive and Headset Applications,” a Presentation From Xilinx and EyeTech Digital Systems

Algorithms, AMD, Medical, Processors, Sensors, Software, Videos / April 11, 2022

Dan Isaacs, Director of Smarter Connected Systems at Xilinx, and Robert Chappell, Founder of EyeTech Digital Systems, co-present the "Implementing Eye Tracking for Medical, Automotive and Headset Applications" tutorial at the May 2015 Embedded Vision Summit. When humans communicate with each other, we get important cues from watching each other’s eyes. Similarly, machines can gain …

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May 2015 Embedded Vision Summit Technical Presentation: “System-level Design for Embedded Vision with FPGA-based Programmable SoCs,” Mario Bergeron, Avnet Electronics Marketing

Algorithms, Avnet, Edge AI and Vision Alliance, Processors, Software, Tools, Videos / May 1, 2022

Mario Bergeron, Technical Marketing Engineer at Avnet Electronics Marketing, presents the "System-Level Design for Embedded Vision with FPGA-based Programmable SoCs" tutorial at the May 2015 Embedded Vision Summit. FPGA-based programmable system-on-chip (SoC) devices offer capabilities beyond those found in traditional embedded processors. The programmability and vast parallel processing capabilities of the FPGA fabric allow developers …

May 2015 Embedded Vision Summit Technical Presentation: “System-level Design for Embedded Vision with FPGA-based Programmable SoCs,” Mario Bergeron, Avnet Electronics Marketing Read More +

May 2015 Embedded Vision Summit Technical Presentation: “3D from 2D: Theory, Implementation, and Applications of Structure from Motion,” Marco Jacobs, videantis

Algorithms, Processors, Software, Tools, videantis, Videos / January 25, 2020

Marco Jacobs, Vice President of Marketing at videantis, presents the "3D from 2D: Theory, Implementation, and Applications of Structure from Motion" tutorial at the May 2015 Embedded Vision Summit. Structure from motion uses a unique combination of algorithms that extract depth information using a single 2D moving camera. Using a calibrated camera, feature detection, and …

May 2015 Embedded Vision Summit Technical Presentation: “3D from 2D: Theory, Implementation, and Applications of Structure from Motion,” Marco Jacobs, videantis Read More +

May 2015 Embedded Vision Summit Technical Presentation: “Low-power Embedded Vision: A Face Tracker Case Study,” Pierre Paulin, Synopsys

Algorithms, Face Detection, Processors, Software, Synopsys, Tools, Videos / January 25, 2020

Pierre Paulin, R&D Director for Embedded Vision at Synopsys, presents the "Low-power Embedded Vision: A Face Tracker Case Study" tutorial at the May 2015 Embedded Vision Summit. The ability to reliably detect and track individual objects or people has numerous applications, for example in the video-surveillance and home entertainment fields. While this has proven to …

May 2015 Embedded Vision Summit Technical Presentation: “Low-power Embedded Vision: A Face Tracker Case Study,” Pierre Paulin, Synopsys Read More +

“Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation,” a Presentation From Synopsys

Algorithms, Processors, Software, Synopsys, Videos / January 25, 2020

Bruno Lavigueur, Project Leader for Embedded Vision at Synopsys, presents the "Tailoring Convolutional Neural Networks for Low-Cost, Low-Power Implementation" tutorial at the May 2015 Embedded Vision Summit. Deep learning-based object detection using convolutional neural networks (CNN) has recently emerged as one of the leading approaches for achieving state-of-the-art detection accuracy for a wide range of …

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