Algorithms

Free Webinar Explores Deep Learning Model Optimization Techniques for Enhanced On-device AI

On March 23, 2021 at 9 am PT (noon ET), Bibek Chaudhary, research engineer at Nota, will present the free half-hour webinar “Selecting and Combining Deep Learning Model Optimization Techniques for Enhanced On-device AI,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: Model optimization techniques such as […]

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“Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification,” a Presentation from Imagination Technologies

Ana Salazar, Senior Research Manager at Imagination Technologies, presents the “Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification” tutorial at the September 2020 Embedded Vision Summit. This talk explores the challenges of deploying serial computer vision tasks implemented with DNNs. Neural network accelerators have demonstrated significant gains in

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The Battlefield of Cutting Edge Face Detectors

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Face detector is one of the most commonly used AI component today. Whether you are building a system to count the number of people in a room or a home security system that unlocks the door when

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“Sea-thru: A Method for Removing Water from Underwater Images,” a Presentation from the Harbor Branch Oceanographic Institute

Derya Akkaynak, Engineer and Oceanographer at the Harbor Branch Oceanographic Institute, presents the “Sea-thru: A Method for Removing Water from Underwater Images” tutorial at the September 2020 Embedded Vision Summit. Very large underwater image datasets are generated every day that capture important information regarding the state of our oceans, but they cannot be efficiently analyzed

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Where AI Falls Short

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. My colleague Abigail Wen is interviewing some of the greatest minds in artificial intelligence (AI) with her new podcast—Intel on AI. From Ivy-league professors to Fortune 50 executives, I’m pleasantly surprised to hear how many experts in

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“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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“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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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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