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 […]
May 2018 Embedded Vision Summit Slides Read More +
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.
Fei Sun, software engineer at Facebook, delivers the presentation "The Caffe2 Framework for Mobile and Embedded Deep Learning" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. Sun introduces Caffe2, a new open-source machine learning framework, and explains how Facebook is using it to enable computer vision in mobile and embedded devices.
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,
Data Sets for Machine Learning Model Training Read More +
DNNs (deep neural networks) have transformed the field of computer vision, delivering 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, which had been solved quite well with conventional techniques, are now finding even better
Implementing Vision with Deep Learning in Resource-constrained Designs Read More +
The ability to "stitch" together (offline or in real-time) multiple images taken simultaneously by multiple cameras and/or sequentially by a single camera, in both cases capturing varying viewpoints of a scene, is becoming an increasingly appealing (if not necessary) capability in an expanding variety of applications. High quality of results is a critical requirement, one
Computer Vision in Surround View Applications Read More +
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.
Neil Trevett, President of the Khronos Group, delivers the presentation "Update on Khronos Standards for Vision and Machine Learning" at the Embedded Vision Alliance's December 2017 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the deployment of embedded vision and AI.
Dr. Patrick Courtney, MBA, of tec-connection and the Standards in Laboratory Automation (SiLA) Consortium delivers the presentation "The Reverse Factory: Embedded Vision in High-Volume Laboratory Applications" at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum. In his presentation, Courtney covers the following topics: Motivation: the need and the market Big applications today:
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
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