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The listing below showcases the most recently published content associated with various AI and visual intelligence functions.
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“Building A Practical Face Recognition System Using Cloud APIs,” a Presentation from the Washington County Sheriff’s Office
Chris Adzima, Senior Information Systems Analyst for the Washington County Sheriff’s Office in Oregon, presents the “Building a Practical Face Recognition System Using Cloud APIs” tutorial at the May 2018 Embedded Vision Summit. In this presentation, Adzima walks through the design and implementation of a face recognition system utilizing cloud computing and cloud computer vision
The Embedded Vision Summit was held on May 21-24, 2018 in Santa Clara, California, as an educational forum for product creators interested in incorporating visual intelligence into electronic systems and software. The presentations delivered at the Summit are listed below. All of the slides from these presentations are included in… May 2018 Embedded Vision Summit
Mark Bünger, Vice President of Research at Lux Research, delivers the presentation "A New Approach to Mass Transit Security" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. Bünger presents a revolutionary computer-vision-based methodology for public transit safety.
Matt King, Chief Technology Officer at IUNU, delivers the presentation "Instrumenting Greenhouses as Data-driven Manufacturing Facilities" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. King explains how his company is enabling increased efficiency in commercial greenhouses using robotic cameras, computer vision and machine learning.
Deep learning and other machine learning techniques have rapidly become a transformative force in computer vision. Compared to conventional computer vision techniques, machine learning algorithms deliver superior results on functions such as recognizing objects, localizing objects within a frame, and determining which pixels belong to which object. Even problems like optical flow and stereo correspondence,
“Using Computer Vision and Machine Learning to Understand Pet Behavior,” a Presentation from PetCube
Alex Neskin, founder and CTO of PetCube, delivers the presentation "Using Computer Vision and Machine Learning to Understand Pet Behavior" at the Embedded Vision Alliance's December 2017 Vision Industry and Technology Forum. Neskin explains how his start-up is using vision and AI to improve the lives of pets and their owners.
“Using Vision to Collect Rich Data in the Moment of Truth for Retail Analytics and Market Research,” a Presentation from GfK
Dr. Anja Dieckmann of GfK Verein and Markus Iwanczok of GfK SE deliver the presentation "Using Vision to Collect Rich Data in the Moment of Truth for Retail Analytics and Market Research" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In their presentation, Dieckmann and Iwanczok cover the following topics: Market
Erik Klaas of 8tree delivers the presentation "The Evolution of Depth Sensing: From Exotic to Ubiquitous" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Klaas covers the following topics: Why is metrology important? Categorization of common methodologies for dimensional measurements Examples and applications of image-based dimensional measurement Market
This technical article was originally published on Texas Instruments' website (PDF). It is reprinted here with the permission of Texas Instruments. Introduction Cameras are the most precise mechanisms used to capture accurate data at high resolution. Like human eyes, cameras capture the resolution, minutiae and vividness of a scene with such beautiful detail that no
Divya Jain, Technical Director at Tyco Innovation, presents the "End to End Fire Detection Deep Neural Network Platform" tutorial at the May 2017 Embedded Vision Summit. This presentation dives deep into a real-world problem of fire detection to see what it takes to build a complete solution using CNNs. Fire is specifically challenging because it