Andrea Dunbar, Sector Head for Edge AI and Vision at CSEM, presents the “Intelligent Vision System for Grains” tutorial at the May 2021 Embedded Vision Summit. In this presentation, Dunbar discusses the challenges and lessons learned in implementing a custom intelligent vision system to detect types of grain and measure flow rate and morphology of […]
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Marcus Edel, Machine Learning Engineer, and Aaron Boxer, Senior Software Developer, both of Collabora, present the “Super Resolution on Resource Constrained Devices” tutorial at the May 2021 Embedded Vision Summit. Internet video streaming has recently experienced tremendous growth, but delivery quality remains critically dependent on network bandwidth. To mitigate bandwidth limitations, most video is compressed,
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Nathan Kopp, Principal Software Architect for Video Systems at the Chamberlain Group, presents the “Practical Guide to Implementing ML on Embedded Devices” tutorial at the May 2021 Embedded Vision Summit. Deploying machine learning onto edge devices requires many choices and trade-offs. Fortunately, processor designers are adding inference-enhancing instructions and architectures to even the lowest cost
Chris Osterwood, Founder and CEO of Capable Robot Components, presents the “Survey of CMOS Imagers and Lenses—and the Trade-offs You Should Consider” tutorial at the May 2021 Embedded Vision Summit. Selecting the right imager and lens for your vision application is often a daunting challenge due to the vast number of products on the market
Vladimir Haltakov, Self-Driving Car Engineer at BMW Group, presents the “Is My Model Performing Well? It Depends…” tutorial at the May 2021 Embedded Vision Summit. There are many statistical metrics used to measure the performance of machine learning models. While they work well when the model itself is the final product, classical measures are often
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Vladimir Haltakov, Self-Driving Car Engineer at BMW Group, presents the “Data Collection in the Wild” tutorial at the May 2021 Embedded Vision Summit. In scientific papers, computer vision models are usually evaluated on well-defined training and test datasets. In practice, however, collecting high-quality data that accurately represents the real world is a challenging problem. Developing
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Navaneeth Kamballur Kottayil, Lead Machine Learning Developer at AltaML, presents the “Explainability in Computer Vision: A Machine Learning Engineer’s Overview” tutorial at the May 2021 Embedded Vision Summit. With the increasing use of deep neural networks in computer vision applications, it has become more difficult for developers to explain how their algorithms work. This can
Carlo Dal Mutto, Director of Engineering at Airbus, presents the “Productizing Complex Visual AI Systems for Autonomous Flight” tutorial at the May 2021 Embedded Vision Summit. The development of visual AI systems for real-world applications is a complex undertaking characterized by a variety of diverse challenges. While the media spotlight is often focused on academic
Pierre Cambou, Principal Analyst at Yole Développement, presents the “Transformation from Imaging to Sensing: Driving a Market Revolution” tutorial at the May 2021 Embedded Vision Summit. Over the past 20 years, digital imaging has grown to become a huge industry with a focus on producing images for human consumption. More recently, the emphasis has begun
Petronel Bigioi, CTO for Product Licensing at Xperi, presents the “Alternative Image Sensors for Intelligent In-Cabin Monitoring, Home Security and Smart Devices” tutorial at the May 2021 Embedded Vision Summit. The traditional approach for in-cabin-monitoring uses cameras that capture only visible or near-infrared (NIR) light and are designed to represent a scene as closely as
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