Summit 2019

“OpenCV: Current Status and Future Plans,” a Presentation from OpenCV.org

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Satya Mallick, Interim CEO of OpenCV.org, presents the “OpenCV: Current Status and Future Plans” tutorial at the May 2019 Embedded Vision Summit. With over two million downloads per week, OpenCV is the most popular open source computer vision library in the world. It implements over 2500 opt- imized algorithms, works on all major operating systems, […]

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“Improving the Safety and Performance of Automated Vehicles Through Precision Localization,” a Presentation from VSI Labs

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Phil Magney, founder of VSI Labs, presents the “Improving the Safety and Performance of Automated Vehicles Through Precision Localization” tutorial at the May 2019 Embedded Vision Summit. How does a self-driving car know where it is? Magney explains how autonomous vehicles localize themselves against their surroundings through the use of a variety of sensors along

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“AI Reliability Against Adversarial Inputs,” a Presentation from Intel

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Gokcen Cilingir, AI Software Architect, and Li Chen, Data Scientist and Research Scientist, both at Intel, presents the “AI Reliability Against Adversarial Inputs” tutorial at the May 2019 Embedded Vision Summit. As artificial intelligence solutions are becoming ubiquitous, the security and reliability of AI algorithms is becoming an important consideration and a key differentiator for

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“Distance Estimation Solutions for ADAS and Automated Driving,” a Presentation from AImotive

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Gergely Debreczeni, Chief Scientist at AImotive, presents the “Distance Estimation Solutions for ADAS and Automated Driving” tutorial at the May 2019 Embedded Vision Summit. Distance estimation is at the heart of automotive driver assistance systems (ADAS) and automated driving (AD). Simply stated, safe operation of vehicles requires robust distance estimation. Many different types of sensors

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“Accelerate Adoption of AI at the Edge with Easy to Use, Low-power Programmable Solutions,” a Presentation from Lattice Semiconductor

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Hussein Osman, Consumer Segment Manager at Lattice Semiconductor, presents the “Accelerate Adoption of AI at the Edge with Easy to Use, Low-power Programmable Solutions” tutorial at the May 2019 Embedded Vision Summit. In this talk, Osman shows why Lattice’s low-power FPGA devices, coupled with the sensAI software stack, are a compelling solution for implementation of

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“MediaTek’s Approach for Edge Intelligence,” a Presentation from MediaTek

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Bing Yu, Senior Technical Manager and Architect at MediaTek, presents the “MediaTek’s Approach for Edge Intelligence” tutorial at the May 2019 Embedded Vision Summit. MediaTek has incorporated an AI processing unit (APU) alongside the traditional CPU and GPU in its SoC designs for the next wave of smart client devices (smartphones, cameras, appliances, cars, etc.).

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“Can We Have Both Safety and Performance in AI for Autonomous Vehicles?,” a Presentation from Codeplay Software

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Andrew Richards, CEO and Co-founder of Codeplay Software, presents the “Can We Have Both Safety and Performance in AI for Autonomous Vehicles?” tutorial at the May 2019 Embedded Vision Summit. The need for ensuring safety in AI subsystems within autonomous vehicles is obvious. How to achieve it is not. Standard safety engineering tools are designed

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

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

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

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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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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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