Luc Chouinard, AI Specialist and Design Architect at Teledyne Imaging, presents the “Deploying Visual AI on Edge Devices: Lessons From the Real World” tutorial at the May 2022 Embedded Vision Summit. Developing an AI-based edge device is complex, involving hardware, algorithms and software. It requires making many technology-selection decisions and balancing numerous trade-offs. In this […]
Ali Osman Örs, Director of AI ML Strategy and Technologies for Edge Processing at NXP Semiconductors, presents the “Intelligent Vision for the Industrial, Automotive and IoT Edge with the i.MX 8M Plus Applications Processor” tutorial at the May 2022 Embedded Vision Summit. Today’s edge-based ML solutions need a powerful multicore processor packed with features and
On-device intelligence provides important benefits. This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our latest AI research to personalize and adapt models while keeping data private One size doesn’t fit all. The need for intelligent, personalized experiences powered by AI is ever-growing. Our devices are
Enabling On-device Learning at Scale Read More +
Carlos Garcia-Sierra, Product Manager for DeepStream at NVIDIA, presents the “Vision AI At the Edge: From Zero to Deployment Using Low-Code Development” tutorial on behalf of Alvin Clark, Product Marketing Manager at NVIDIA, at the May 2022 Embedded Vision Summit. Development of vision AI applications for the edge presents complex challenges beyond model inference, often
Akhil Docca, Senior Product Marketing Manager at NVIDIA, presents the “Accelerating the Creation of Custom, Production-Ready AI Models for Edge AI,” tutorial at the May 2022 Embedded Vision Summit. AI applications are powered by models. However, creating customized, production-ready AI models requires an army of data scientists and mountains of data. For businesses looking to
This blog post was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. At Tryolabs, we are passionate about building computer vision solutions that have real-world impact. Very often, this means integrating them to run on edge devices. In our journey to master AI on the edge, we have developed
Detecting Safety Helmets in Real-time Read More +
On August 30, 2022 at 9 am PT (noon ET), Jenny Plunkett, Senior Developer Relations Engineer at Edge Impulse, and Armaghan Ebrahimi, Partner Solutions Engineer at Sony Electronics Professional Solutions Americas, will present the free hour webinar “Edge Impulse’s FOMO Technology and Sony’s Computer Vision Platform: A Compelling Combination,” organized by the Edge AI and
Dave Tokic, Vice President of Marketing and Strategic Partnerships at Algolux, presents the “Optimizing Camera Image Quality to Maximize Computer Vision Results” tutorial at the May 2022 Embedded Vision Summit. Applications of computer vision have broadly expanded thanks to deep learning, which achieves much better results than classical techniques. This is evident in our cell
Nathan Wheeler, Chairman and CEO, and Tony Luce, Vice President of Product Marketing, both of Network Optix, present the “Platform Approach to Developing Networked Visual AI Systems” tutorial at the May 2022 Embedded Vision Summit. Connected cameras are becoming ubiquitous. Coupled with CV and ML, they enable a growing range of applications that monitor people,
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models’ size and complexity while taking advantage of hardware acceleration for inference. For these
Neural Network Optimization with AIMET Read More +
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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