Todd Poole, Director of Venture Capital Investments for HPE Pathfinder Ventures, presents the “Navigating the Evolving Venture Capital Landscape for Edge AI Start-ups” tutorial at the May 2023 Embedded Vision Summit. The venture capital environment has undergone a huge shift in the past year. In this talk, Poole explains how the VC landscape has changed […]
Jack Narcotta, Principal Analyst for the Smart Home at Omdia, presents the “Advanced Presence Sensing: What It Means for the Smart Home” tutorial at the May 2023 Embedded Vision Summit. Eventually, homes will become highly autonomous—powered by ubiquitous, connected, intelligent devices (sometimes referred to as ambient computing)—but this remains a distant vision. In the meantime,
“Advanced Presence Sensing: What It Means for the Smart Home,” a Presentation from Omdia Read More +
Yoav Banin, Chief Product and Business Development Officer, and Tahmida Mahmud, Engineering Manager for Perception, both of Nauto, presents the “Tracking and Fusing Diverse Risk Factors to Drive a SAFER Future” tutorial at the May 2023 Embedded Vision Summit. Unless you’re a gang member or drug addict, driving is your top risk. But which risks
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. In the field of artificial intelligence, vector databases are an emerging database technology that is transforming how we represent and analyze data by using vectors — multi-dimensional numerical arrays — to capture the semantic relationships between data
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Haran Thanigasalam, Camera and Imaging Consultant to the MIPI Alliance, presents the “MIPI CSI-2 Image Sensor Interface Standard Features Enable Efficient Embedded Vision Systems” tutorial at the May 2023 Embedded Vision Summit. As computer vision applications continue to evolve rapidly, there’s a growing need for a smarter standardized interface connecting multiple image sensors to processors
Haran Thanigasalam, Camera and Imaging Consultant to the MIPI Alliance, presents the “Introduction to the MIPI CSI-2 Image Sensor Interface Standard” tutorial at the May 2023 Embedded Vision Summit. By taking advantage of select features in standardized interfaces, vision system architects can help reduce processor load, cost and power consumption while gaining flexibility to source
Dwith Chenna, Senior Embedded DSP Engineer for Computer Vision at Magic Leap, presents the “Practical Approaches to DNN Quantization” tutorial at the May 2023 Embedded Vision Summit. Convolutional neural networks, widely used in computer vision tasks, require substantial computation and memory resources, making it challenging to run these models on resource-constrained devices. Quantization involves modifying
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Travis Davis, Delivery Manager in the Automation and Autonomy Core, and Tarik Loukili, Technical Lead for Automation and Autonomy Applications, both of John Deere, present the “Reinventing Smart Cities with Computer Vision” tutorial at the May 2023 Embedded Vision Summit. John Deere uses machine learning and computer vision (including stereo vision) for challenging outdoor applications
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Samuel Örn, Team Lead and Senior Machine Learning and Computer Vision Engineer at Invision AI, presents the “Using a Collaborative Network of Distributed Cameras for Object Tracking” tutorial at the May 2023 Embedded Vision Summit. Using multiple fixed cameras to track objects requires a careful solution design. To enable scaling the number of cameras, the
Rustem Feyzkhanov, Staff Machine Learning Engineer at Instrumental, presents the “Survey of Model Compression Methods” tutorial at the May 2023 Embedded Vision Summit. One of the main challenges when deploying computer vision models to the edge is optimizing the model for speed, memory and energy consumption. In this talk, Feyzkhanov provides a comprehensive survey of
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