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Summit 2018

NXP Semiconductors Demonstration of Optimized Performance and Memory Utilization for Object Detection on i.MX RT

Markus Levy, Director of Enabling Technologies at NXP Semiconductors, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Levy demonstrates the i.MX RT architecture, which represents the convergence of low-power application processors and high-performance microcontrollers. This particular demo shows the i.MX RT1050 MCU, which is based on a 600MHz Arm® Cortex®-M7 core […]

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AImotive Scales Toward Productization of Self-Driving Technology

Ferenc Pintér, Head of Software at AImotive, provides a company update at the May 2018 Embedded Vision Summit. Specifically, Pintér explains how AImotive‘s technological approach and development pipeline support the creation of scalable autonomous solutions. After discussing the fundamental effect of simulation of self-driving development, Pintér introduces aiSim and aiWare, two AImotive technologies and winners

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Intel Demonstration of Scalable Deep Learning-based Face Detection and Recognition with FPGAs

Richard Chuang, Global Platform Solutions Architect at Intel, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Chuang demonstrates an end-to-end face detection and recognition reference solution using the OpenVINO toolkit. Four primary algorithms are running in this demo system on top of OpenVINO: face detection, landmark detection, feature extraction, and face

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Intel Demonstration of High Performance Vision Deployment – The OpenVINO Toolkit in Action

Soren Knudsen, Video and Software Ecosystem Accelerant at Intel, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Knudsen demonstrates how you can get top performance for vision solutions using Intel’s OpenVINO™ toolkit (open visual inference and neural network optimization), part of the Intel® Vision Products portfolio. View heterogeneous workload performance across

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Intel Demonstration of Flexible Options to Speed Vision Workloads – A Heterogeneous Approach

Jeffrey McAllister, Technical Consulting Engineer at Intel, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, McAllister demonstrates how with Intel’s OpenVINO™ toolkit, (open visual inference and neural network optimization), you can boost workload performance with easy heterogeneous execution across multiple types of Intel® platforms (CPU, CPU with integrated graphics, FPGAs, and

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Lattice Semiconductor Demonstration of a Deep Neural Network that Consumes Only ~800 uW

Abdullah Raouf, Marketing Manager for Low Power Solutions at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Raouf demonstrates what an ultra-small (2.15 mm x 2.55 mm), $1 USD FPGA is able to do when embedded with the the company’s sensAI BNN accelerator IP. With the demonstrated solution, system

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Lattice Semiconductor Demonstration of Speed Sign Detection Using ECP5 and Machine Learning

JP Singh, Automotive Marketing manager at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Singh demonstrates a machine learning CNN implemented using the company’s sensAI stack on a ECP5 FPGA. Singh shows the detection of speed limit signs and the determination of speed limits with a CNN implementation that

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Lattice Semiconductor Demonstration of Object Counting Using ECP5 and Machine Learning

Dirk Seidel, Senior Industrial Marketing Manager at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Seidel demonstrates object counting using machine learning with a CNN implementation based on Lattice’s sensAI stack and the ECP5 FPGA. Seidel shows how Lattice’s small form factor, low power and production-priced ECP5 FPGA can

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Lattice Semiconductor Demonstration of Human Presence Detection at the Edge

Tom Watzka, Marketing Manager and Mobile Systems Architect at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Watzka demonstrates how the Lattice ECP5 FPGA can support Human Presence Inferencing at the IoT edge. This inferencing engine leverages the Lattice sensAI tool flow to deliver real-time performance with sub-1W power

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Intel Demonstration of Deep Learning Inference Performance at the Edge with the OpenVINO Toolkit

Saumya Satish, from the Computer Vision team at Intel, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Satish discusses how developers can build high performance computer vision applications and integrate deep learning inference with Intel’s OpenVINO™ (open visual inference and neural network optimization) toolkit. The toolkit helps streamline deep learning deployments

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