Object Identification Functions
“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… “A Mask Detection Smart Camera
“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 Detection and Dataset Labeling
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
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
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
September 2020 Embedded Vision Summit Slides
The Embedded Vision Summit was held online on September 15-25, 2020, California, 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.… September 2020 Embedded Vision Summit
“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.
“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
“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
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
“Safer and More Efficient Intersections with Computer Vision,” a Presentation from Cubic | GRIDSMART
Jeff Price, Vice President and General Manager at Cubic | GRIDSMART, presents the “Safer and More Efficient Intersections with Computer Vision” tutorial at the September 2020 Embedded Vision Summit. GRIDSMART is an edge computer vision system that uses omnidirectional imaging to detect and track objects through intersections to optimize traffic signal timing in response to
“Deep Learning for Manufacturing Inspection: Case Studies,” a Presentation from FLIR Systems
Stephen Se, Senior Research Manager at FLIR Systems, presents the “Deep Learning for Manufacturing Inspection: Case Studies” tutorial at the September 2020 Embedded Vision Summit. Deep learning has revolutionized artificial intelligence and has been shown to provide the best solutions to many problems in computer vision, image classification, speech recognition and natural language processing. See
“Practical Image Data Augmentation Methods for Training Deep Learning Object Detection Models,” a Presentation from EJ Technology Consultants
Evan Juras, Computer Vision Engineer at EJ Technology Consultants, presents the “Practical Image Data Augmentation Methods for Training Deep Learning Object Detection Models” tutorial at the September 2020 Embedded Vision Summit. Data augmentation is a method of expanding deep learning training datasets by making various automated modifications to existing images in the dataset. The resulting
New June Oven Designed with MediaTek’s i500 AIoT Platform Delivers a Smart Cooking Experience to Consumers
MediaTek’s i500 brings powerful computer vision, advanced multimedia and fast Wi-Fi to the third-generation June Oven HSINCHU, Taiwan – December 14, 2020 –MediaTek today announced that the company’s i500 AIoT chipset platform is the main processor inside the new June Oven, a twelve-in-one countertop convection oven. MediaTek’s i500 has a dedicated AI Processing Unit (APU)
Face Mask Detection in Street Camera Video Streams Using AI: Behind the Curtain
This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. In the new world of coronavirus, multidisciplinary efforts have been organized to slow the spread of the pandemic. The AI community has also been a part of these endeavors. In particular, developments for monitoring social distancing or identifying
Object Recognition: 3 Things You Need to Know
This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. What Is Object Recognition? Object recognition is a computer vision technique for identifying objects in images or videos. Object recognition is a key output of deep learning and machine learning algorithms. When humans look at a photograph or
What Is Object Detection?
This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. 3 Things You Need to Know Object detection is a computer vision technique for locating instances of objects in images or videos. Object detection algorithms typically leverage machine learning or deep learning to produce meaningful results. When humans
“Object Detection for Embedded Markets,” a Presentation from Imagination Technologies
Paul Brasnett, PowerVR Business Development Director for Vision and AI at Imagination Technologies, presents the “Object Detection for Embedded Markets” tutorial at the May 2019 Embedded Vision Summit. While image classification was the breakthrough use case for deep learning-based computer vision, today it has a limited number of real-world applications. In contrast, object detection is
