Summit 2018

Synopsys Demonstration of Android Neural Network Acceleration with EV6x

Gordon Cooper, product marketing manager, and Mischa Jonker, software engineer, both of Synopsys, deliver a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Cooper and Jonker demonstrate how the DesignWare EV6x Embedded Vision Processor with deep learning can offload application processor tasks to increase performance and reduce power consumption, using an Android Neural […]

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Cadence Demonstration of On-Device AI for Image Classification

Megha Daga, senior technical marketing manager at Cadence, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Daga demonstrates the highly capable Tensilica Vision P6 DSP, which does both computer vision and AI processing. The demo showcases Cadence’s automatic code generation tool for neural networks, the Xtensa Neural Network Compiler, which accepts

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Cadence Demonstration of On-Device AI for Object Detection

Megha Daga, senior technical marketing manager at Cadence, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Daga demonstrates the power of the Tensilica Vision P6 DSP to perform both computer vision and AI processing. The demo detects all the faces in the camera view using the Tiny Yolo V2 network, and

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Arm Demonstration of Image Classification Using Arm NN and the Compute Library

Gian Marco Iodice, Senior Software Engineer at Arm, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Iodice demonstrates image classification using Arm NN and the Compute Library, showing how they provide Arm-based platforms with the flexibility to switch between the CPU and GPU for easy and performant image classification.

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Arm Demonstration of the Company’s Object Detection Processor

Alexey Lopich, Principal Hardware Engineer and Team Lead at Arm, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Lopich demonstrates Arm’s Object Detection processor, showing how it detects objects – from 50×60 pixels to full screen – in real time, at high speed (60fps) and in high resolution (Full HD). He

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Horizon Robotics Demonstration of Its Autonomous Driving Platform Powered by Its Embedded AI Chip

Su Li, Senior Technical Account Manager at Horizon Robotics, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Li demonstrates the company’s autonomous driving computing platform, Matrix, based on Horizon Robotics’ self-developed embedded AI processor architecture, BPU2.0. Matrix has powerful perceptual computing capability and can provide high-performance sensing system for L4 autonomous

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Horizon Robotics Demonstration of Its Smart City Solution Powered by Its Embedded AI Chip

Su Li, Senior Technical Account Manager at Horizon Robotics, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Li demonstrates the company’s smart city solution using a surveillance video analytic system. Based on the Sunrise AI processor, an embedded AI computer vision chip developed by the company, Horizon Robotics uses a cutting-edge

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Horizon Robotics Demonstration of Its Smart Retail Solution Powered by Its Embedded AI Chip

Su Li, Senior Technical Account Manager at Horizon Robotics, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Li demonstrates the company’s smart retail solution using an AI-based face recognition camera, which can capture a maximum of 200 faces per frame, detect at 1080p full-frame rate and identify the age and gender

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Boulder AI Demonstration of Its GPU-enabled DNNCam (Deep Neural Network Camera)

Darren Odom, CEO of Boulder AI, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Odom demonstrates DNNCam, an intelligent GPU-enabled deep-learning neural network camera that is waterproof, dust-proof and runs AI algorithms at the image source. The Boulder AI edge camera executes AI/machine learning frameworks and computer vision algorithms without additional

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NXP Semiconductors Demonstration of Deep Learning-based Multi-object Detection Using S32V234 Vision Processor

Ali Osman Ors, Director of AI Strategy and Partnerships for Automotive at NXP Semiconductors, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Ors demonstrates deep learning-based multi-object detection based on MobileNet and Single Shot Detector (SSD) running in real-time on the embedded automotive-grade S32V234 Vision SoC, with the capability of detecting

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PO Box #4446
Walnut Creek, CA 94596

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