Au-Zone Technologies

Demonstration of Pedestrian Detection and Classification

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This pedestrian detection and classification demonstration showcases the DeepView Model Pack and Maivin AI Vision Starter Kit, both developed by Au-Zone Technologies. The Maivin AI Vision Starter Kit is a modular AI smart camera platform built on NXP’s i.MX8MPlus applications processors and production-grade hardware and software components to enable rapid prototyping and field deployment of […]

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Shortcut to Series Production: Modular Maivin i.MX 8M Plus AI Vision Kit from AU-Zone, Toradex and Vision Components

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July 28, 2021 – For proof of concept, rapid prototyping and small series production, AU-Zone and Toradex, working in close cooperation with Vision Components, have developed the modular Maivin i.MX 8M Plus AI Vision Kit. The developer kit is based on a Toradex Verdin i.MX 8M Plus System-on-Module and a carrier board, which AU-Zone designed

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Machine Learning Goes Mainstream – NXP’s eIQ ML Software Development Environment Just Got Smarter and Friendlier

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This blog post was originally published by NXP Semiconductors. It is reprinted here with the permission of NXP Semiconductors. Edge intelligence is one of the most disruptive innovations since the advent of the Internet of Things (IoT). While the IoT gave rise to billions of smart, connected devices transmitting countless terabytes of sensor data for

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Upcoming Webinar Explores Rapid Machine Learning Model Development

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On July 8, 2021 at 8:00 am PT (11:00 am ET), Alliance Member company NXP will deliver the free webinar “Data To Inference In Under 30 Minutes: Machine Learning Development With Nxp eIQ Software”, in partnership with fellow Alliance Member company Au-Zone Technologies. From the event page: No matter your experience level or the data

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“Tools and Techniques for Optimizing DNNs on Arm-based Processors with Au-Zone’s DeepView ML Toolkit,” a Presentation from Au-Zone Technologies

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Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, presents the “Tools and Techniques for Optimizing DNNs on Arm-based Processors with Au-Zone’s DeepView ML Toolkit” tutorial at the May 2019 Embedded Vision Summit. In this presentation, Taylor describes methods and tools for developing, profiling and optimizing neural network solutions for deployment on Arm MCUs, CPUs and

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“Harnessing the Edge and the Cloud Together for Visual AI,” a Presentation from Au-Zone Technologies

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Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, presents the “Harnessing the Edge and the Cloud Together for Visual AI” tutorial at the May 2018 Embedded Vision Summit. Embedded developers are increasingly comfortable deploying trained neural networks as static elements in edge devices, as well as using cloud-based vision services to implement visual intelligence remotely.

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“Deploying CNN-based Vision Solutions on a $3 Microcontroller,” a Presentation from Au-Zone Technologies

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Greg Lytle, VP of Engineering at Au-Zone Technologies, presents the “Deploying CNN-based Vision Solutions on a $3 Microcontroller” tutorial at the May 2018 Embedded Vision Summit. In this presentation, Lytle explains how his company designed, trained and deployed a CNN-based embedded vision solution on a low-cost, Cortex-M-based microcontroller (MCU). He describes the steps taken to

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Implementing Vision with Deep Learning in Resource-constrained Designs

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DNNs (deep neural networks) have transformed the field of computer vision, delivering superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence, which had been solved quite well with conventional techniques, are now finding even better

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“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies

Algorithms, Au-Zone Technologies, Automotive, NXP Semiconductors, Object Identification, Optical Character Recognition, Processors, Software, Tools, Videos /

Rafal Malewski, Head of the Graphics Technology Engineering Center at NXP Semiconductors, and Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, present the "Implementing an Optimized CNN Traffic Sign Recognition Solution" tutorial at the May 2017 Embedded Vision Summit. Now that the benefits of using deep neural networks for image classification are well known, the

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“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies

Algorithms, Au-Zone Technologies, Automotive, NXP Semiconductors, Object Identification, Optical Character Recognition, Processors, Software, Tools, Videos /

Rafal Malewski, Head of the Graphics Technology Engineering Center at NXP Semiconductors, and Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, present the "Implementing an Optimized CNN Traffic Sign Recognition Solution" tutorial at the May 2017 Embedded Vision Summit. Now that the benefits of using deep neural networks for image classification are well known, the

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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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Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596

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Phone: +1 (925) 954-1411
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