Object Identification

“A Mask Detection Smart Camera Using the NVIDIA Jetson Nano: System Architecture and Developer Experience,” a Presentation from BDTI and Tryolabs

Evan Juras, Computer Vision Engineer at BDTI, and Braulio Ríos, Machine Learning Engineer at Tryolabs, co-present the “A Mask Detection Smart Camera Using the NVIDIA Jetson Nano: System Architecture and Developer Experience” tutorial at the May 2021 Embedded Vision Summit. MaskCam is a prototype reference design for a smart camera that counts the number of […]

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“Object Detection and Dataset Labeling Using Colors of Manufactured Objects,” a Presentation from BASF

Ian Childers, Head of Technology for Functional Coatings—Object Recognition at BASF, presents the “Object Detection and Dataset Labeling Using Colors of Manufactured Objects” tutorial at the May 2021 Embedded Vision Summit. This talk introduces a new method for object detection for consumer goods and other applications based on measuring an object’s illumination invariant fluorescent chroma.

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NVIDIA Research: Fast Uncertainty Quantification for Deep Object Pose Estimation

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Researchers from NVIDIA, University of Texas at Austin and Caltech developed a simple, efficient, and plug-and-play uncertainty quantification method for the 6-DoF (degrees of freedom) object pose estimation task, using an ensemble of K pre-trained estimators with

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Struggles of Running Object Detection on a Raspberry Pi

Frustrated man (Image by Gerd Altmann from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Have you ever been so excited after reading a how-to tutorial or a github readme file, only to discover after following it through that it is not really as

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BDTI, Jabil, NVIDIA and Tryolabs Demonstration of AI-based Face Mask Detection and Analytics

BDTI and its partners, Tryolabs S.A. and Jabil Optics, are delighted to announce MaskCam: an open-source smart camera prototype reference design based on the NVIDIA Jetson Nano capable of estimating the number and percentage of people wearing face masks in its field of view. MaskCam was developed as part of an independent, hands-on evaluation of

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September 2020 Embedded Vision Summit Slides

The Embedded Vision Summit was held online on September 15-25, 2020, as an educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations delivered at the Summit are listed below. All of the slides from these presentations are included in PDF form. To… September 2020 Embedded Vision Summit

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“Tackling Extreme Visual Conditions for Autonomous UAVs In the Wild,” a Presentation from Skydio

Hayk Martiros, Head of Autonomy at Skydio, presents the “Tackling Extreme Visual Conditions for Autonomous UAVs In the Wild” tutorial at the September 2020 Embedded Vision Summit. Skydio ships autonomous robots that are flown at scale in complex, unknown environments every day to capture incredible video, automate dangerous inspections and save lives of first responders.

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“Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking,” a Presentation from Seedland

Kit Thambiratnam, General Manager of the Seedland AI Center, presents the “Multi-modal Re-identification: IOT + Computer Vision for Residential Community Tracking” tutorial at the September 2020 Embedded Vision Summit. The recent COVID-19 outbreak necessitated monitoring in communities such as tracking of quarantined residents and tracking of close-contact interactions with sick individuals. High-density communities also have

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“Image-Based Deep Learning for Manufacturing Fault Condition Detection,” a Presentation from Samsung

Jake Lee, Principal Engineer and Head of the Machine Learning Group at Samsung, presents the “Image-Based Deep Learning for Manufacturing Fault Condition Detection” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Lee explores applying deep learning to analyzing manufacturing parameter data to detect fault conditions. The manufacturing parameter data contains multivariate time

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Building and Deploying a Face Mask Detection Application Using NGC Collections

This technical article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. AI workflows are complex. Building an AI application is no trivial task, as it takes various stakeholders with domain expertise to develop and deploy the application at scale. Data scientists and developers need easy access to software

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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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