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May 2024 Embedded Vision Summit Opening Remarks (May 22)

Jeff Bier, Founder of the Edge AI and Vision Alliance, welcomes attendees to the May 2024 Embedded Vision Summit on May 22, 2024. Bier provides an overview of the edge AI and vision market opportunities, challenges, solutions and trends. He also introduces the Edge AI and Vision Alliance and the… May 2024 Embedded Vision Summit […]

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“Understand the Multimodal World with Minimal Supervision,” a Keynote Presentation from Yong Jae Lee

Yong Jae Lee, Associate Professor in the Department of Computer Sciences at the University of Wisconsin-Madison and CEO of GivernyAI, presents the “Learning to Understand Our Multimodal World with Minimal Supervision” tutorial at the May 2024 Embedded Vision Summit. The field of computer vision is undergoing another profound change. Recently,… “Understand the Multimodal World with

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“Market and Technology Trends in Automotive ADAS,” a Presentation from the Yole Group

Florian Domengie, Senior Technology and Market Analyst at the Yole Group, presents the “Market and Technology Trends in Automotive ADAS” tutorial at the May 2024 Embedded Vision Summit. In this talk, Domengie takes an in-depth look at the rapidly advancing and fast-growing space of driver assistance and autonomous driving. He… “Market and Technology Trends in

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“Recent Trends in Industrial Machine Vision: Challenging Times,” a Presentation from the Yole Group

Axel Clouet, Technology and Market Analyst for Imaging at the Yole Group, presents the “Recent Trends in Industrial Machine Vision: Challenging Times” tutorial at the May 2024 Embedded Vision Summit. For decades, cameras have been increasingly used in industrial applications as key components for automation. After two years of rapid… “Recent Trends in Industrial Machine

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“Camera Interface Standards for Embedded Vision Applications,” an Interview with the MIPI Alliance

Haran Thanigasalam, Camera and Imaging Consultant for the MIPI Alliance, talks with Shung Chieh, Senior Vice President at Eikon Systems, for the “Exploring MIPI Camera Interface Standards for Embedded Vision Applications” interview at the May 2024 Embedded Vision Summit. This insightful interview delves into the relevance and impact of MIPI… “Camera Interface Standards for Embedded

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“Identifying and Mitigating Bias in AI,” a Presentation from Intel

Nikita Tiwari, AI Enabling Engineer for OEM PC Experiences in the Client Computing Group at Intel, presents the “Identifying and Mitigating Bias in AI” tutorial at the May 2024 Embedded Vision Summit. From autonomous driving to immersive shopping, and from enhanced video collaboration to graphic design, AI is placing a… “Identifying and Mitigating Bias in

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“The Fundamentals of Training AI Models for Computer Vision Applications,” a Presentation from GMAC Intelligence

Amit Mate, Founder and CEO of GMAC Intelligence, presents the “Fundamentals of Training AI Models for Computer Vision Applications” tutorial at the May 2024 Embedded Vision Summit. In this presentation, Mate introduces the essential aspects of training convolutional neural networks (CNNs). He discusses the prerequisites for training, including models, data… “The Fundamentals of Training AI

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“An Introduction to Semantic Segmentation,” a Presentation from Au-Zone Technologies

Sébastien Taylor, Vice President of Research and Development for Au-Zone Technologies, presents the “Introduction to Semantic Segmentation” tutorial at the May 2024 Embedded Vision Summit. Vision applications often rely on object detectors, which determine the nature and location of objects in a scene. But many vision applications require a different… “An Introduction to Semantic Segmentation,”

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“Augmenting Visual AI through Radar and Camera Fusion,” a Presentation from Au-Zone Technologies

Sébastien Taylor, Vice President of Research and Development for Au-Zone Technologies, presents the “Augmenting Visual AI through Radar and Camera Fusion” tutorial at the May 2024 Embedded Vision Summit. In this presentation Taylor discusses well-known limitations of camera-based AI and how radar can be leveraged to address these limitations. He… “Augmenting Visual AI through Radar

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“DNN Quantization: Theory to Practice,” a Presentation from AMD

Dwith Chenna, Member of the Technical Staff and Product Engineer for AI Inference at AMD, presents the “DNN Quantization: Theory to Practice” tutorial at the May 2024 Embedded Vision Summit. Deep neural networks, widely used in computer vision tasks, require substantial computation and memory resources, making it challenging to run… “DNN Quantization: Theory to Practice,”

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