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Application Processor Unit (APU) Quarterly Market Monitor

Application processor: All-in-one solution for the computing challenges of the next decade MARKET DYNAMICS: 2019 APU market closed with total revenue of $31B. Seasonally weak Q1-20 expected to remain above $7B even as COVID-19 stresses the supply chain. Cost & ASP declines at ~20% per year through 2021; slowing to ~10% per year for 2022+. […]

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Edge AI and Vision Insights: March 31, 2020 Edition

MEDICAL APPLICATIONS Deep Learning for Medical Imaging: COVID-19 (Novel Coronavirus) Detection In this guest blog post published by MathWorks, Dr. Barath Narayanan from the University of Dayton Research Institute, along with his colleague Dr. Russell C. Hardie from the University of Dayton, provide a detailed description of how to implement a deep learning-based technique for

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Synopsys Online Embedded Vision Sessions: Navigating Intelligent Vision at the Edge

In these online sessions from Synopsys’ recent workshop, you’ll learn about the latest trends in artificial intelligence and computer vision and how to use embedded vision technologies to navigate from concept to successful silicon. You’ll get a deep dive into deep learning, embedded vision, and standards-based programming for automotive, mobile, surveillance, and consumer applications. Below

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Huiying Medical: Helping Combat COVID-19 with AI Technology

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. The COVID-19 coronavirus, since its initial outbreak in Wuhan, China, has quickly become a global pandemic, as declared by the World Health Organization (WHO). The number of confirmed cases has exceeded 577,531 globally as of March 27,

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“OpenCV: Past, Present and Future,” a Presentation from OpenCV.org

Gary Bradski, the President and CEO of OpenCV.org, delivers the presentation “OpenCV: Past, Present and Future” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Bradski shares the latest developments in the OpenCV open source library for computer vision and deep learning applications, as well as where OpenCV is heading.

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Maximize CPU Inference Performance with Improved Threads and Memory Management in Intel Distribution of OpenVINO Toolkit

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. The popularity of convolutional neural network (CNN) models and the ubiquity of CPUs means that better inference performance can deliver significant gains to a larger number of users than ever before. As multi-core processors become the norm,

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BrainChip and Socionext Provide a New Low-Power Artificial Intelligence Platform for AI Edge Applications

Business Wire – March 23, 2020 – BrainChip Holdings Ltd (ASX: BRN), a leading provider of ultra-low power high performance AI technology, today announced that Socionext Inc., a leader in advanced SoC solutions for video and imaging systems, will offer customers an Artificial Intelligence Platform that includes the Akida SoC, an ultra-low power high performance

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“Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets,” a Presentation from Yole Développement

John Lorenz, Market and Technology Analyst for Computing and Software at Yole Développement, delivers the presentation “Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Lorenz presents Yole Développement’s latest analysis on the evolution of

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CEVA Announces DSP and Voice Neural Networks Integration with TensorFlow Lite for Microcontrollers

WhisPro™ speech recognition software for voice wake words and custom command models now available with open source TensorFlow Lite for Microcontrollers implementing machine learning at the edge TensorFlow Lite for Microcontrollers from Google is already optimized and available for CEVA-BX DSP cores, accelerating the use of low power AI in conversational and contextual awareness applications

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Deep Learning for Medical Imaging: COVID-19 Detection

This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. I’m pleased to publish another post from Barath Narayanan, University of Dayton Research Institute (UDRI), LinkedIn Profile. Co-author: Dr. Russell C. Hardie, University of Dayton (UD) Dr. Barath Narayanan graduated with MS and Ph.D. degree in Electrical Engineering

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