Object Identification

Hailo Demonstration of State-of-the-Art Object Detection on the Edge with the Hailo-8 AI Processor

Nadav Eden, Technical Account Manager at Hailo, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Eden demonstrates state-of-the-art object detection on the edge with the Hailo-8 AI processor. YoloV5m is a high-end neural network model for object detection, a fundamental computer vision task. The Hailo-8 […]

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Hailo Demonstration of Leveraging High Processor Throughput to Improve Object Detection on the Edge

Yaniv Sulkes, Vice President of Product Marketing and Automotive at Hailo, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Sulkes demonstrates how to leverage the high throughput of the Hailo-8 AI processor in order to improve large-scale object detection on the edge. The high throughput

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Cadence Demonstration of Vision and AI Applications on Tensilica-based Platforms

Amol Borkar, Senior Product Marketing Manager for Vision and AI DSPs at Cadence, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Borkar demonstrates various vision and AI applications, including real-time examples of driver monitoring, automotive perception, 6DoF SLAM and semantic segmentation, running on Tensilica processor-

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Blaize Demonstration of Sensor Fusion and Semantic Segmentation Processing on the Pathfinder P1600

Doug Watt, Director of Field Applications Engineering at Blaize, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Watt demonstrates sensor fusion and semantic segmentation processing on the Blaize Pathfinder P1600. The use case fuses data received from full HD cameras and from lidar and radar

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Blaize Demonstration of Multi-camera Object Detection on the Blaize Xplorer X1600E

Shawn Holiday, Senior Director for Customer Success at Blaize, demonstrates the company’s latest edge AI and vision technologies and products at the 2021 Embedded Vision Summit. Specifically, Holiday demonstrates multi-camera object detection on the Blaize Xplorer X1600E. The use case processes 5 independent HD video streams using 5 independent YoloV3 networks with less than 100

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May 2021 Embedded Vision Summit Slides

The Embedded Vision Summit was held online on May 25-28, 2021, 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… May 2021 Embedded Vision Summit

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“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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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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