Videos

“The Four Key Trends Driving the Proliferation of Visual Perception,” a Presentation from the Embedded Vision Alliance

Jeff Bier, Founder of the Embedded Vision Alliance and Co-founder and President of BDTI, presents the “Four Key Trends Driving the Proliferation of Visual Perception” tutorial at the May 2018 Embedded Vision Summit. With so much happening in computer vision applications and technology, and happening so fast, it can be difficult to see the big […]

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Synopsys Demonstration of YOLO v2-based Object Detection and Identification

Jon Talbot, Field Applications Engineer in the Solutions Group at Synopsys, demonstrates the company’s latest embedded vision technologies and products at the February 2018 Embedded World conference. Specifically, Talbot demonstrates a YOLO (You Only Look Once) v2 CNN graph used for object detection and identification. Deep learning inference is running on the combination of a

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“A New Approach to Mass Transit Security,” a Presentation from Lux Research

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.

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“Evaluating Early Stage Investment Opportunities in Camera-First Innovations,” a Presentation from Shasta Ventures

Jacob Mullins, Partner at Shasta Ventures, delivers the presentation "Evaluating Early Stage Investment Opportunities in Camera-First Innovations" at the Embedded Vision Alliance's March 2018 Vision Industry and Technology Forum. Mullins explains why his firm views the camera as an increasingly central link between the physical and digital worlds.

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“Instrumenting Greenhouses as Data-driven Manufacturing Facilities,” a Presentation from IUNU

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.

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Arm Demonstration of Applications using CMSIS-NN and the Arm Compute Library

Tim Hartley, Senior Product Manager at Arm, demonstrates the company’s latest embedded vision technologies and products at the March 2018 Embedded Vision Alliance Vision Industry and Technology Forum. Specifically, Hartley demonstrates various example applications built using Arm software development tools. CMSIS-NN provides a library of low level machine learning primitives targeting Arm Cortex®-M microcontrollers. Hartley

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Xilinx Demonstration of Quad-Video Analytics with Real-time, Multi-CNN Recognition Acceleration

Dale Hitt, Director of Strategic Market Development at Xilinx, demonstrates the company’s latest embedded vision technologies and products at the March 2018 Embedded Vision Alliance Vision Industry and Technology Forum. Specifically, Hitt demonstrates real-time video analytics on four video streams on a single Xilinx ZU9 MPSoC. Each video stream is processed with a different CNN

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Renesas Demonstration of a Caffe-based CNN for Object Identification

Ganesh Balamitran, Product Marketing Manager at Renesas Electronics, demonstrates the company’s latest embedded vision technologies and products at the March 2018 Embedded Vision Alliance Vision Industry and Technology Forum. Specifically, Balamitran demonstrates a Caffe-based CNN for object identification. The demonstration was developed by Renesas partner Uncanny Vision using the Uncanny DLL libraries. This demonstration is

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“The Caffe2 Framework for Mobile and Embedded Deep Learning,” a Presentation from Facebook

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.

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