Brian Dipert

“Memory-centric Hardware Acceleration for Machine Intelligence,” a Presentation from Crossbar

Sylvain Dubois, Vice President of Business Development and Marketing at Crossbar, presents the “Memory-centric Hardware Acceleration for Machine Intelligence” tutorial at the May 2019 Embedded Vision Summit. Even the most advanced AI chip architectures suffer from performance and energy efficiency limitations caused by the memory bottleneck between computing cores and data. Most state-of-the-art CPUs, GPUs, […]

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Framos AI Launches FAIM SDK with 2D/3D Skeleton Tracking Functionality

September 10, 2019 – Framos AI GmbH, a member of the FRAMOS® Group, leading global supplier of imaging products, custom vision solutions and OEM services, is launching its FAIM SDK to enable AI-powered algorithms optimized for real-time applications. Skeleton tracking is the first functionality that is integrated into the Framos AI SDK, which enables efficient

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“DNN Challenges and Approaches for L4/L5 Autonomous Vehicles,” a Presentation from Graphcore

Tom Wilson, Vice President of Automotive at Graphcore, presents the “DNN Challenges and Approaches for L4/L5 Autonomous Vehicles” tutorial at the May 2019 Embedded Vision Summit. The industry has made great strides in development of L4/L5 autonomous vehicles, but what’s available today falls far short of expectations set as recently as two to three years

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Embedded Vision Insights: September 10, 2019 Edition

LETTER FROM THE EDITOR Dear Colleague, Deep Learning for Computer Vision with TensorFlow 2.0 is the Embedded Vision Alliance's in-person, hands-on technical training class. The next session will take place November 1 in Fremont, California, hosted by Alliance Member company Mentor. This one-day hands-on overview will give you the critical knowledge you need to develop

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“Snapdragon Hybrid Computer Vision/Deep Learning Architecture for Imaging Applications,” a Presentation from Qualcomm

Robert Lay, Computer Vision and Camera Product Manager at Qualcomm, presents the “Snapdragon Hybrid Computer Vision/Deep Learning Architecture for Imaging Applications” tutorial at the May 2019 Embedded Vision Summit. Advances in imaging quality and features are accelerating, thanks to hybrid approaches that combine classical computer vision and deep learning algorithms and that take advantage of

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“Dynamically Reconfigurable Processor Technology for Vision Processing,” a Presentation from Renesas

Yoshio Sato, Senior Product Marketing Manager in the Industrial Business Unit at Renesas, presents the “Dynamically Reconfigurable Processor Technology for Vision Processing” tutorial at the May 2019 Embedded Vision Summit. The Dynamically Reconfigurable Processing (DRP) block in the Arm Cortex-A9 based RZ/A2M MPU accelerates image processing algorithms with spatially pipelined, time-multiplexed, reconfigurable- hardware compute resources.

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iniVation

IniVation Announces Launch of DV Software 1.0

05 September 2019 – iniVation is pleased to announce the release of DV Software 1.0, created to accelerate application development for its revolutionary event-based Dynamic Vision Sensor technology. The modular structure of the DV software allows developers to combine pre-built modules into applications faster than ever before. DV Software 1.0 offers many advantages for developers,

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Machine Vision: MVTec Advances Standardization

MVTec has been participating in the development of important machine vision standards since 2005 The focus is on interoperability and 3D vision Process automation and machine vision are merging Munich, September 05, 2019 – To mark its 33rd meeting with the GenICam Standard Group during the IVSM (International Vision Standards Meeting, October 7 to 11 in Stresa,

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“Eye Tracking for the Future: The Eyes Have It,” a Presentation from Parallel Rules

Peter Milford, President of Parallel Rules, presents the “Eye Tracking for the Future: The Eyes Have It” tutorial at the May 2019 Embedded Vision Summit. Eye interaction technologies complement augmented and virtual reality head-mounted displays. In this presentation, Milford reviews eye tracking technology, concentrating mainly on camera-based solutions and associated system requirements. Wearable eye tracking

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