Edge AI and Vision Alliance

Edge AI and Vision Insights: October 27, 2021 Edition

LETTER FROM THE EDITOR Dear Colleague, The next Embedded Vision Summit will take place as a live event from May 17-19, 2022 in Santa Clara, California. The Embedded Vision Summit is the key event for system and application developers who are incorporating computer vision and visual AI into products. It attracts a unique audience of […]

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“Person Re-Identification and Tracking at the Edge: Challenges and Techniques,” a Presentation from the University of Auckland

Morteza Biglari-Abhari, Senior Lecturer at the University of Auckland, presents the “Person Re-Identification and Tracking at the Edge: Challenges and Techniques” tutorial at the May 2021 Embedded Vision Summit. Numerous video analytics applications require understanding how people are moving through a space, including the ability to recognize when the same person has moved outside of

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“DNN Training Data: How to Know What You Need and How to Get It,” a Presentation from Tech Mahindra

Abhishek Sharma, Practice Head for Engineering AI at Tech Mahindra, presents the “DNN Training Data: How to Know What You Need and How to Get It” tutorial at the May 2021 Embedded Vision Summit. Successful training of deep neural networks requires the right amounts and types of annotated training data. Collecting, curating and labeling this

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“Automotive Vision – What’s Growing, What’s Not, and Why?,” a Presentation from Strategy Analytics

Ian Riches, Vice President of Automotive Practice and Director at Strategy Analytics, presents the “Automotive Vision Systems – What’s Growing, What’s Not, and Why?” tutorial at the May 2021 Embedded Vision Summit. In this presentation, Riches looks at the key applications and use cases that are driving rapid adoption of vision systems in automotive applications,

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“A Highly Data-Efficient Deep Learning Approach,” a Presentation from Samsung

Patrick Bangert, Vice President of AI at Samsung, presents the “Highly Data-Efficient Deep Learning Approach” tutorial at the May 2021 Embedded Vision Summit. Many applications, such as medical imaging, lack the large amounts of data required for training popular CNNs to achieve sufficient accuracy. Often, these same applications suffer from an imbalanced class distribution problem

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“Challenges in Vision-based Adaptive Traffic Control Systems,” a Presentation from Sahaj Software Solutions

Venkatesh Wadawadagi, Solution Consultant at Sahaj Software Solutions, presents the “Challenges in Vision-based Adaptive Traffic Control Systems” tutorial at the May 2021 Embedded Vision Summit. Adaptive traffic control systems (ATCSs) adjust traffic signal timing based on demand. Wadawadagi begins by presenting the main building blocks of a vision-based ATCS, including pre-processing, vehicle detection, vehicle classification

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“10 Things You Must Know Before Designing Your Own Camera,” a Presentation from Panopteo

Alex Fink, consultant at Panopteo, presents the “10 Things You Must Know Before Designing Your Own Camera” tutorial at the May 2021 Embedded Vision Summit. Computer vision requires vision. This is why companies that use computer vision often decide they need to create a custom camera module (and perhaps other custom sensors) that meets the

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“Maintaining DNN Accuracy When the Real World is Changing,” a Presentation from Observa

Erik Chelstad, CTO and co-founder of Observa, presents the “Maintaining DNN Accuracy When the Real World is Changing” tutorial at the May 2021 Embedded Vision Summit. We commonly train deep neural networks (DNNs) on existing data and then use the trained model to make predictions on new data. Once trained, these predictive models approximate a

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“Deploying PyTorch Models for Real-time Inference On the Edge,” a Presentation from Nomitri

Moritz August, CDO at Nomitri GmbH, presents the “Deploying PyTorch Models for Real-time Inference On the Edge” tutorial at the May 2021 Embedded Vision Summit. In this presentation, August provides an overview of workflows for deploying compressed deep learning models, starting with PyTorch and creating native C++ application code running in real-time on embedded hardware

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“Computer Vision for the Built Environment,” a Presentation from Nomad Go

David Greschler, CEO and co-founder of Nomad Go, presents the “Computer Vision for the Built Environment” tutorial at the May 2021 Embedded Vision Summit. Facilities and operations managers of buildings, college campuses, retail and foodservice establishments all struggle to answer one fundamental question: “What are people doing in our spaces?” Computer vision – specifically edge

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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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