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Parallel Processing Using Python for Faster Video Processing

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. How can we speed up video processing? Parallel processing is the answer! If you want to process a number of video files, it might take from minutes to hours, depending on the size of the video, frame …

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DNN-Based Object Detectors

This article was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Unlike image classifiers, which simply report on the most important objects within an image, object detectors determine where objects of interest are located, their sizes and class labels within an image. Consequently, object detectors are central …

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Quanergy LiDAR 3D Object Detection Works with Nx

This video was originally published at Network Optix’ website. It is reprinted here with the permission of Network Optix. Quanergy LiDAR solutions provide actionable insights to organizations across major industries and enable partners and their end-users to deploy innovative solutions to drive their business growth and ultimately, improve the quality of life for people around …

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Magical OpenVINO Integration with TensorFlow

This video was originally published at Intel’s YouTube channel. It is reprinted here with the permission of Intel. In this episode, Ragesh and Steph talk about OpenVINO™ Integration with Tensorflow which is used for speeding up inferencing of a TensorFlow based real-time application at the edge. Ragesh pulls and runs a docker image on his …

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Leading Research Delivers AI Firsts

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Qualcomm AI Research establishes firsts in AI across research and proof-of-concept. At Qualcomm, we have a culture of innovation. We take pride in researching and developing fundamental technologies that will change the world. It’s also in our …

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Further Pascal VOC 2012 Exploration and Plans for the Future

This blog post was originally published at Hasty’s website. It is reprinted here with the permission of Hasty. The previous post featuring our results on the PASCAL VOC 2012 cleansing project was successful. We attracted your attention and got you talking about the Data-centric AI development approach on Reddit and the Slack communities. There was …

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Visionary.ai Demonstration of True Night Vision Technology

Althea Mirvis, Vice President of Marketing at Visionary.ai, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Mirvis demonstrates the company’s True Night Vision technology. The demo showcases Visionary.ai’s extremely low light performance. Two cameras with identical hardware are placed inside a box, one using a …

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EYYES Demonstration of AI Technologies for a Safer World

Dr. Wolfgang Domann, Managing Director, and Dipl.-Ing. Johannes Traxler, CEO, both of EYYES GmbH, demonstrate the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Domann and Traxler demonstrate the company’s product range. EYYES provides a full stack of technology to create complete AI products and solutions. The …

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Visidon Demonstration of a Driver Monitoring System Running On a Synopsys ARC EV7x Processor

Vaida Jasulaityte, Business Development Director at Visidon, demonstrates the company’s latest edge AI and vision technologies and products in Synopsys’ booth at the 2022 Embedded Vision Summit. Specifically, Jasulaityte demonstrates Visidon’s Driver Monitoring System (DMS) running on a Synopsys ARC® EV7x Vision Processor. In the demo, Jasulaityte shows how Visidon’s DMS, a vehicle safety system, …

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Exploring AIMET’s Quantization-aware Training Functionality

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. In Exploring AIMET’s Post-Training Quantization Methods, we discussed Cross-layer Equalization (CLE), Bias Correction, and AdaRound in AIMET. Using these methods, the weights and activations of neural network models can be reduced to lower bit-width representations, thus reducing …

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