Technical Insights

“Accuracy: Beware of Red Herrings and Black Swans,” a Presentation from Perceive

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Steve Teig, CEO of Perceive, presents the “Accuracy: Beware of Red Herrings and Black Swans” tutorial at the September 2020 Embedded Vision Summit. Machine learning aims to construct models that are predictive: accurate even on data not used during training. But how should we assess accuracy? (Hint: simply computing the average error on a pre-determined […]

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“Recent Advances in Post-training Quantization,” a Presentation from Intel

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Alexander Kozlov, Deep Learning R&D Engineer at Intel, presents the “Recent Advances in Post-training Quantization” tutorial at the September 2020 Embedded Vision Summit. The use of low-precision arithmetic (8-bit and smaller data types) is key for the deployment of deep neural network inference with high performance, low cost and low power consumption. Shifting to low-precision

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“The Future of Image Sensors,” An Embedded Vision Summit Expert Panel Discussion

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Shung Chieh, Co-founder and Vice President of Engineering at Solidspac3, moderates the “Future of Image Sensors” Expert Panel at the September 2020 Embedded Vision Summit. Other panelists include Sandor Barna, Vice President of Hardware at Aurora; Boyd Fowler, Chief Technology Officer at OmniVision; Sundar Ramamurthy, Group Vice President and General Manager at Applied Materials; and

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“Practical Approaches to Training Data Strategy: Bias, Legal and Ethical Considerations,” a Presentation from Samasource

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Audrey Jill Boguchwal, Senior Product Manager at Samasource, presents the “Practical Approaches to Training Data Strategy: Bias, Legal and Ethical Considerations” tutorial at the May 2019 Embedded Vision Summit. Recent McKinsey research cites the top five limitations that prevent companies from adopting AI technology. Training data strategy is a common thread. Companies face challenges obtaining

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“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

Algorithms, Automotive, Edge AI and Vision Alliance, Processors, Sensors and Cameras, Software, Summit 2019, Tools, Videos /

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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“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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“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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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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