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Summit 2020

“Safer and More Efficient Intersections with Computer Vision,” a Presentation from Cubic | GRIDSMART

Jeff Price, Vice President and General Manager at Cubic | GRIDSMART, presents the “Safer and More Efficient Intersections with Computer Vision” tutorial at the September 2020 Embedded Vision Summit. GRIDSMART is an edge computer vision system that uses omnidirectional imaging to detect and track objects through intersections to optimize traffic signal timing in response to […]

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“CMOS Image Sensors: A Guide to Building the Eyes of a Vision System,” a Presentation from GoPro

Jon Stern, Director of Optical Systems at GoPro, presents the “CMOS Image Sensors: A Guide to Building the Eyes of a Vision System” tutorial at the September 2020 Embedded Vision Summit. Improvements in CMOS image sensors have been instrumental in lowering barriers for embedding vision into a broad range of systems. For example, a high

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“Deep Learning on Mobile Devices,” a Presentation from Siddha Ganju

Independent AI architect Siddha Ganju  presents the “Deep Learning on Mobile Devices” tutorial at the September 2020 Embedded Vision Summit. Over the last few years, convolutional neural networks (CNNs) have grown enormously in popularity, especially for computer vision. Many applications running on smartphones and wearable devices could benefit from the capabilities of CNNs. However, CNN’s

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“Deep Learning for Manufacturing Inspection: Case Studies,” a Presentation from FLIR Systems

Stephen Se, Senior Research Manager at FLIR Systems, presents the “Deep Learning for Manufacturing Inspection: Case Studies” tutorial at the September 2020 Embedded Vision Summit. 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. See

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“Practical DNN Quantization Techniques and Tools,” a Presentation from Facebook

Raghuraman Krishnamoorthi, Software Engineer at Facebook, presents the “Practical DNN Quantization Techniques and Tools” tutorial at the September 2020 Embedded Vision Summit. Quantization is a key technique to enable the efficient deployment of deep neural networks. In this talk, Krishnamoorthi presents an overview of techniques for quantizing convolutional neural networks for inference with integer weights

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“Can You Patent Your AI-Based Invention?,” a Presentation from Fitch, Even, Tabin & Flannery LLP

Thomas Lebens, Partner at Fitch, Even, Tabin & Flannery LLP, presents the “Can You Patent Your AI-Based Invention?” tutorial at the September 2020 Embedded Vision Summit. Patenting inventions is one way to capitalize on the hard work and creativity that drives an innovative product, but recent cases have made things difficult for innovators whose inventions

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“Practical Image Data Augmentation Methods for Training Deep Learning Object Detection Models,” a Presentation from EJ Technology Consultants

Evan Juras, Computer Vision Engineer at EJ Technology Consultants, presents the “Practical Image Data Augmentation Methods for Training Deep Learning Object Detection Models” tutorial at the September 2020 Embedded Vision Summit. Data augmentation is a method of expanding deep learning training datasets by making various automated modifications to existing images in the dataset. The resulting

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“Video Activity Recognition with Limited Data for Smart Home Applications,” a Presentation from Comcast

Hongcheng Wang, Director of Technical Research at Comcast, presents the “Video Activity Recognition with Limited Data for Smart Home Applications” tutorial at the September 2020 Embedded Vision Summit. Comcast’s Xfinity Home connects millions of home smart cameras and IoT devices to improve its customers’ safety and security. The company’s teams use computer vision and deep

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“Deploying AI Software to Embedded Devices Using Open Standards,” a Presentation from Codeplay Software

Andrew Richards, Co-founder and CEO of Codeplay Software, presents the “Deploying AI Software to Embedded Devices Using Open Standards” tutorial at the September 2020 Embedded Vision Summit. AI software developers need to deploy diverse classes of algorithms in embedded devices, including deep learning, machine vision and sensor fusion. Adapting these algorithms to run efficiently on

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“Combining CNNs and Conventional Algorithms for Low-Compute Vision: A Case Study in the Garage,” a Presentation from the Chamberlain Group

Nathan Kopp, Principal Software Architect for Video Systems at the Chamberlain Group, presents the “Combining CNNs and Conventional Algorithms for Low-Compute Vision: A Case Study in the Garage” tutorial at the September 2020 Embedded Vision Summit. Chamberlain Group (CGI) is a global leader in access control solutions with its Chamberlain and LiftMaster garage door opener

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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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