Dear Colleague,2021 Embedded Vision Summit

It can be hard finding the right people and best technology when you’re creating leading-edge computer vision and edge AI-enabled products… but we have an incredible opportunity for you to connect directly with suppliers and learn about the latest building-block technologies. It’s happening at the virtual 2021 Embedded Vision Summit, and it’s the perfect gateway to propel your current or next project. Plus, there will be 80+ highly relevant, top-quality sessions to gain technical know-how and the latest insights. Check out the expanding list of sponsors and exhibitors to see who you’d like to connect with. Next, learn more about the keynote from UC Berkeley Professor Pieter Abbeel, the general session presentations from Edge Impulse’s Zach Shelby and Qualcomm’s Ziad Asghar, and all of the other exciting presentations and activities at the Summit. And then register today with promo code EARLYBIRDNL21 to receive your 15%-off Early Bird Discount!

Brian Dipert
Editor-In-Chief, Edge AI and Vision Alliance


Reinforcement Learning: a Practical IntroductionMicrosoft
In this presentation, Joe Booth, former Vice President of Engineering at Orions Systems (now part of Microsoft, where Booth is a Principal Group Engineering Manager) and an independent researcher, explains how reinforcement learning relates to other machine learning methods, provides examples of real-world deployments, and gives a technical overview of the elements of reinforcement learning. Booth also presents practical advice on when to use reinforcement learning and how to structure problems to use reinforcement learning effectively. Finally, he provides the recommended resources for learning more about this important technique.

Federated Edge Computing System ArchitecturesIntel
With ever-increasing amounts of video and other sensor data, and growing requirements for privacy and low latency, inferencing at the edge is increasingly attractive. But there are many ways to allocate and coordinate computing resources for edge inferencing. For example, to achieve scale and fault tolerance, design principles from cloud computing can be applied to create compute clusters at the edge that are managed by the cloud, an approach called “federated computing.” In this talk, Vaidyanathan Krishnamoorthy, Edge Inference Solutions Architect at Intel, explores a range of edge computing system architectures, with a focus on federated computing. He illustrates how these system architectures utilize Intel CPUs and accelerators to address real-world use cases in retail and industrial applications.


Image-Based Deep Learning for Manufacturing Fault Condition DetectionSamsung
In this presentation, Jake Lee, Principal Engineer and Head of the Machine Learning Group at Samsung, explores applying deep learning to analyzing manufacturing parameter data to detect fault conditions. The manufacturing parameter data contains multivariate time series sensor signals from a fabrication line. Due to practical manufacturing limitations, datasets are often incomplete, imbalanced and/or not well-formed for deep learning models. To overcome these challenges, Samsung applies new data augmentation methods to train a deep CNN for fault condition classification using deep generative models. Lee also proposes an efficient method to convert multiple time series sensor inputs into a two-dimensional image representation to enable the use of image-based CNNs. Samsung’s experiment results show the fault classification accuracy improvement obtained by applying these techniques.

Deep Learning for Manufacturing Inspection: Case StudiesFLIR
Deep learning has revolutionized artificial intelligence and has been shown to provide the best solutions to many problems in computer vision, image classification, speech recognition and natural language processing. In this talk, Stephen Se, Senior Research Manager at FLIR Systems (now part of Teledyne Technologies), presents highlights from his experience in deep learning machine vision applications such as manufacturing inspection, defect detection and classification. Deep learning has gained significant attention in the machine vision industry because it does not require the complex algorithm development required for traditional rule-based image processing techniques. Se covers the deep learning workflow from data collection to training and deployment, including transfer learning. Se also presents a few case studies from manufacturing inspection applications.


Embedded Vision Summit: May 25-28, 2021

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Vision Systems DesignVision Systems Design
Vision Systems Design is the machine vision and imaging-resource for engineers and integrators worldwide. Receive unique, unbiased and in-depth technical information about the design of machine vision and imaging systems for demanding applications in your inbox today.


Attend the Embedded Vision Summit to meet these and other leading computer vision and edge AI technology suppliers!

Algolux provides technologies that enable the smart optimization of computer vision systems, transforming the development and accuracy of machines that can “see”. The company’s CRISP technology addresses the cost, schedule, and expertise challenges that product development teams face in optimizing their imaging and vision systems.


BASF has developed a vision system that captures color and surface chemistry data to identify consumer packaged goods and apparel articles at the SKU level. The color-based object detection system can also automatically capture and label images used for visual AI model training.


BDTI is the industry’s trusted source for analysis, advice, and engineering for embedded processing technology and applications. For over 25 years, BDTI has helped companies develop, choose, and use signal processing technology. BDTI has deep experience in computer vision and deep learning.


Blaize’s compute solution unites silicon and software to optimize AI from the edge to the core. The company is partnering with customers to transform their products so they can deliver better experiences and better lives; its first products, the Blaize Pathfinder and Xplorer platforms and the Blaize AI Software Suite, are now available.


BrainChip is a leading provider of neuromorphic computing solutions, a type of artificial intelligence that is inspired by the biology of the human neuron. The Company’s revolutionary new spiking neural network technology can learn autonomously, evolve and associate information just like the human brain.


Cadence enables global electronic design innovation and plays an essential role in the creation of today’s integrated circuits and electronics. Customers use Cadence software, hardware, IP, and services to design and verify advanced semiconductors and systems.


CEVA is a public licensor of signal processing platforms and AI processors for a smarter, connected world. The company partners with semiconductor companies and OEMs to create power-efficient, intelligent and connected devices for a range of end markets, including mobile, consumer, automotive, industrial and IoT.


Coherent LogixCoherent Logix
Coherent Logix designs and manufactures memory-networked processors that enable 100% software programmability in real-time at low power, latency and price. The company’s HyperX technology efficiently and securely processes large amounts of data in parallel and can be scaled to fit any core, edge, or mobile applications.


Edge ImpulseEdge Impulse
Edge Impulse is a leading development platform for machine learning on edge devices. The company’s mission is to enable every developer and device maker with the best development and deployment experience for machine learning on the edge, focusing on sensor, audio, and computer vision applications.


Intel is an industry leader, creating world-changing technology that enables global progress and enriches lives. Inspired by Moore’s Law, Intel continuously works to advance the design and manufacturing of semiconductors to help address its customers’ greatest challenges.


QualcommMicrosoft M12
For more than 30 years, Qualcomm has served as the essential accelerator of wireless technologies and the ever-growing mobile ecosystem. Now our inventions are set to transform other industries by bringing connectivity, machine vision and intelligence to billions of machines and objects, catalyzing the IoT.


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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