Summit 2019

“AI-powered Identity: Evaluating Face Recognition Capabilities,” a Presentation From the University of Houston

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Ioannis Kakadiaris, Distinguished University Professor of Computer Science at the University of Houston, presents the "AI-powered Identity: Evaluating Face Recognition Capabilities" tutorial at the May 2019 Embedded Vision Summit. Following the deep learning renaissance, the face recognition community has achieved remarkable results when comparing images that are both frontal and non-occluded. However, significant challenges remain […]

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“Designing Home Monitoring Cameras for Scale,” a Presentation from Ring

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Ilya Brailovskiy, Principal Engineer, and Changsoo Jeong, Head of Algorithm, both of Ring, present the "Optimizing SSD Object Detection for Low-power Devices" tutorial at the May 2019 Embedded Vision Summit. In this talk, Brailovskiy and Jeong discuss how Ring designs smart home video cameras to make neighborhoods safer. In particular, they focus on three key

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“Low-power Computer Vision: Status, Challenges and Opportunities,” a Presentation from Purdue University

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Professor Yung-Hsiang Lu of Purdue University presents the "Low-power Computer Vision: Status, Challenges and Opportunities" tutorial at the May 2019 Embedded Vision Summit. Energy efficiency plays a crucial role in making computer vision successful in battery-powered systems, including drones, mobile phones and autonomous robots. Since 2015, IEEE has been organizing an annual competition on low-power

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“Optimizing SSD Object Detection for Low-power Devices,” a Presentation from Allegro

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Moses Guttmann, CTO and founder of Allegro, presents the "Optimizing SSD Object Detection for Low-power Devices" tutorial at the May 2019 Embedded Vision Summit. Deep learning-based computer vision models have gained traction in applications requiring object detection, thanks to their accuracy and flexibility. For deployment on low-power hardware, single-shot detection (SSD) models are attractive due

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“What’s Changing in Autonomous Vehicle Investments Worldwide — and Why?,” a Presentation from Woodside Capital Partners

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Rudy Burger, Managing Partner at Woodside Capital Partners, presents the "What’s Changing in Autonomous Vehicle Investments Worldwide—and Why?" tutorial at the May 2019 Embedded Vision Summit. So far, over $100B has been invested by industry into the development of autonomous vehicles (AVs), and the pace of investment has recently accelerated. In this talk, Burger presents

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“Making Cars That See — Failure is Not an Option,” a Presentation from Synopsys

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Burkhard Huhnke, Vice President of Automotive Strategy for Synopsys, presents the "Making Cars That See—Failure is Not an Option" tutorial at the May 2019 Embedded Vision Summit. Drivers are the biggest source of uncertainty in the operation of cars. Computer vision is helping to eliminate human error and make the roads safer. But 14 years

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“Three Key Factors for Successful AI Projects,” a Presentation from MathWorks

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Bruce Tannenbaum, Technical Marketing Manager for AI applications at MathWorks, presents the "Three Key Factors for Successful AI Projects" tutorial at the May 2019 Embedded Vision Summit. AI is transforming the products we build and the way we do business. AI using images and video is already at work in our smart home devices, our

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“Using Deep Learning for Video Event Detection on a Compute Budget,” a Presentation from PathPartner Technology

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Praveen Nayak, Tech Lead at PathPartner Technology, presents the "Using Deep Learning for Video Event Detection on a Compute Budget" tutorial at the May 2019 Embedded Vision Summit. Convolutional neural networks (CNNs) have made tremendous strides in object detection and recognition in recent years. However, extending the CNN approach to understanding of video or volumetric

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“Can Simulation Solve the Training Data Problem?,” a Presentation from Mindtech

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Peter McGuinness, Vice President of AI and Services at Mindtech, presents the "Can Simulation Solve the Training Data Problem?" tutorial at the May 2019 Embedded Vision Summit. While there has been rapid progress in the adoption of neural networks and the evolution of neural network structures, the problem of training data remains. Even companies with

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“Mining Site Data Extraction Using 3D Machine Learning,” a Presentation from Strayos

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Ravi Sahu, Founder and CEO of Strayos, presents the "Mining Site Data Extraction Using 3D Machine Learning" tutorial at the May 2019 Embedded Vision Summit. This talk focuses on extracting invariant features for segmentation of 3D models of mining sites. The image data is generated by stitching together geo-tagged images from a drone. The 3D

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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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