Technical Insights

“Building an Autonomous Detect-and-Avoid System for Commercial Drones,” a Presentation from Iris Automation

Alejandro Galindo, Head of Research and Development at Iris Automation, presents the “Building an Autonomous Detect-and-Avoid System for Commercial Drones” tutorial at the May 2021 Embedded Vision Summit. Commercial and industrial drones have the potential to completely disrupt industries and create new ones. Used in applications such as infrastructure inspection, search and rescue, package delivery, […]

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“Efficient Deep Learning for 3D Point Cloud Understanding,” a Presentation from Facebook

Bichen Wu, Research Scientist at Facebook Reality Labs, presents the “Efficient Deep Learning for 3D Point Cloud Understanding” tutorial at the May 2021 Embedded Vision Summit. Understanding the 3D environment is a crucial computer vision capability required by a growing set of applications such as autonomous driving, AR/VR and AIoT. 3D visual information, captured by

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“Intelligent Vision System for Grains,” a Presentation from CSEM

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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“Super Resolution on Resource Constrained Devices,” a Presentation from Collabora

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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“A Practical Guide to Implementing ML on Embedded Devices,” a Presentation from the Chamberlain Group

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

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“Is My Model Performing Well? It Depends…,” a Presentation from BMW Group

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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“Explainability in Computer Vision: A Machine Learning Engineer’s Overview,” a Presentation from AltaML

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

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“Productizing Complex Visual AI Systems for Autonomous Flight,” a Presentation from Airbus

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

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“Alternative Image Sensors for Intelligent In-Cabin Monitoring, Home Security and Smart Devices,” a Presentation from Xperi

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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“How Containerization Unblocks Barriers to Fast, Easy Deployment of AI-Driven Visual Recognition Applications,” a Presentation from Camio

Rakshit Agrawal, Director of Research and Development at Camio, presents the “How Containerization Unblocks Barriers to Fast, Easy Deployment of AI-Driven Visual Recognition Applications” tutorial at the May 2021 Embedded Vision Summit. Recent progress in machine learning algorithms has been meteoric. Yet their implementation in real-world embedded applications crawls at a snail’s pace, in large

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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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