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Arm Continues to Accelerate IoT Software Development with New Partnerships

News highlights: Arm development tools integrated into GitHub Actions enabling faster time to market for IoT and embedded developers Qeexo and Nota.AI integrate Arm Virtual Hardware for better accessibility and ease-of-deployment of ML workloads A year ago we unveiled Arm Virtual Hardware, a cloud-based offering that delivers virtual models of Arm subsystems and third-party development …

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Free Webinar Explores How to Implement AI-based Analytics for VMS

On February 7, 2023 at 9 am PT (noon ET), Avi Baum, CTO, and Mark Grobman, Machine Learning CTO, both of Hailo, will present the free hour webinar “Implementing Advanced AI-based Analytics for Video Management Systems,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: The term video …

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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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Voxel51 Demonstration of Visual Dataset Management and Analysis with FiftyOne

Jason Corso, CEO and Co-founder of Voxel51, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Corso demonstrates the importance of well-honed data workflows for computer vision dataset management and the value of visual data analysis to improve model performance. Corso describes both the rich python …

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Renesas Demonstration of MPU Evaluation Using the Vision AI Cloud Platform

Manny Singh, Product Marketing Manager at Renesas Electronics, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Singh demonstrates how RZ/V series microprocessors (MPUs) can be evaluated with remote boards using a cloud platform. Singh shows how easily the vision AI performance of the MPU, including …

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Deci Demonstration of How to Build State-of-the-art Computer Vision Models with Deci’s NAS Platform

Ofer Baratz, AI Product Manager at Deci, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Baratz demonstrates how to build state-of-the-art computer vision models using the Deci platform powered by hardware-aware neural architecture search technology. With Deci’s platform, AI teams can easily build fast and …

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Deci Demonstration of Real-time Object Detection on a NVIDIA Jetson SoC with DeciDet

Nave Assaf, Deep Learning Engineer at Deci, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Assaf demonstrates how the DeciDet model runs real-time object detection on eight video streams connected to one Nvidia Jetson device while outperforming YOLO X both in terms of accuracy and …

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Fire Detected, Fire Banned

Automatic forest fire detection system with AI enables early and efficient fire fighting Heat waves caused by climate change are currently also increasing strongly across Europe and the associated risk of forest fires is rising immensely. Fires in natural areas are increasingly getting out of control due to drought or wind, and the risk of …

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Synaptics Demonstration of the High-performance Multi-core Katana Edge AI SoC

Ananda Roy, Senior Product Manager leading the low-power AI product line at Synaptics, demonstrates the company’s latest edge AI and vision technologies and products at the 2022 Embedded Vision Summit. Specifically, Roy demonstrates the Katana SoC, a high-performance multi-core processor that does AI inferencing for both audio and vision at ultra-low power consumption levels. The …

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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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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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