May 2016 Embedded Vision Summit Replay

Conference Presentation Slides

2016 Embedded Vision Summit Slides
(81 MB—click to download.)

Conference Overview Presentations

Welcome Remarks and Conference Overview (Day 1)
Jeff Bier, Embedded Vision Alliance

Welcome Remarks and Conference Overview (Day 2)
Jeff Bier, Embedded Vision Alliance

Keynote and Plenary Session Presentations

"Large-Scale Deep Learning for Building Intelligent Computer Systems"
Jeff Dean, Google

"Using Vision to Enable Autonomous Land, Sea and Air Vehicles"
Larry Matthies, NASA JPL

"Computer Vision 2.0: Where We Are and Where We're Going"
Jeff Bier, Embedded Vision Alliance

Business Insights Track Presentations

"How Computer Vision Is Accelerating the Future of Virtual Reality"
Allen Rush, AMD

"Lessons Learned from Bringing Mobile and Embedded Vision Products to Market"
Tim Harley, ARM

"Understanding Camera Subsystems for Your Embedded Vision System and Making the Right Choice"
Gerrit Fischer, Basler

"The Road Ahead for Neural Networks: Five Likely Surprises"
Chris Rowen, Cadence

"A Practitioner’s Guide to Commercializing Applications of Computer Vision"
Peter Shannon, Firelake Capital Management

"Making Existing Cars Smart Via Embedded Vision and Deep Learning"
Stefan Heck, NAUTO

"Sensing Technologies for the Autonomous Vehicle"
Tom Wilson, NXP Semiconductors

"Is Vision the New Wireless?"
Raj Talluri, Qualcomm Technologies

"Should Visual Intelligence Reside in the Cloud or at the Edge? Trade-offs in Privacy, Security and Performance"
Andreas Gal, Silk Labs

"How Deep Learning Is Enabling Computer Vision Markets"
Bruce Daley, Tractica

"Computer Vision in Cars: Status, Challenges, and Trends"
Marco Jacobs, videantis

"Democratizing Computer Vision Development: Lessons from the Video Game Industry"
Paul Kruszewski, WRNCH

"What's Hot in Embedded Vision for Investors?"
Panel Discussion: Intel Capital, Bank of America Merrill Lynch, Vision Ventures, TandemLaunch and Firelake Capital Management

Vision Tank Competition Finalist Presentations
3DiVi, 8tree, Magik Eye, Preemadonna, and SKUR

Enabling Technologies Track Presentations

"Fast Deployment of Low-power Deep Learning on CEVA Vision Processors"
Yair Siegel, CEVA

"Digital Gimbal: Rock-steady Video Stabilization without Extra Weight!"
Petronel Bigioi, FotoNation

"TensorFlow: Enabling Mobile and Embedded Machine Intelligence"
Pete Warden, Google

"Efficient Convolutional Neural Network Inference on Mobile GPUs"
Paul Brasnett, Imagination Technologies

"Accelerating Deep Learning Using Altera FPGAs"
Bill Jenkins, Intel

"NVIDIA VisionWorks, a Toolkit for Computer Vision"
Elif Albuz, NVIDIA

"High-resolution 3D Reconstruction on a Mobile Processor"
Michael Mangan, Qualcomm

"Using the OpenCL C Kernel Language for Embedded Vision Processors"
Seema Mirchandaney, Synopsys

Technical Insights Track Presentations

"Using SGEMM and FFTs to Accelerate Deep Learning"
Gian Marco Iodice, ARM

"Semantic Segmentation for Scene Understanding: Algorithms and Implementations"
Nagesh Gupta, Auviz Systems

"Video Stabilization Using Computer Vision: Techniques for Embedded Devices"
Ben Weiss, CEVA

"Getting from Idea to Product with 3D Vision"
Anavai Ramesh, Intel and Avinash Nehemiah, MathWorks

"Real-world Vision Systems Design: Challenges and Techniques"
Yury Gorbachev, Itseez

"The Vision API Maze: Options and Trade-offs,"
Neil Trevett, Khronos Group

"Making Computer Vision Software Run Fast on Your Embedded Platform,"
Alexey Rybakov, LUXOFT

"Dataflow: Where Power Budgets Are Won and Lost"
Sofiane Yuos, Movidius

"Computational Photography: Understanding and Expanding the Capabilities of Standard Cameras"
Orazio Gallo, NVIDIA

"Image Sensors for Vision: Foundations and Trends"
Robin Jenkin, ON Semiconductor

"The OpenCV Open Source Computer Vision Library: What’s New and What’s Coming?"
Gary Bradski, OpenCV Foundation

"Programming Embedded Vision Processors Using OpenVX"
Pierre Paulin, Synopsys

Technology Showcase Demonstrations

3DiVi

3DiVi

AdasWorks

AdasWorks

Almalence

Almalence

Analog Devices

Analog Devices

ARM

ARM

ARM

ARM

Auviz Systems

Auviz Systems

BDTI

BDTI

BDTI

BDTI

BDTI

BDTI

Cadence

Cadence

Cadence

Cadence

CEVA

CEVA

FotoNation

FotoNation

HSA Foundation

HSA Foundation

HSA Foundation

HSA Foundation

Huawei

Huawei

Intel

Intel

Intel

Intel

IRIDA Labs

IRIDA Labs

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

Luxoft

MathWorks

MathWorks

MIPI Alliance

MIPI Alliance

Morpho

Morpho

Movidius

Movidius

NVIDIA

NVIDIA

NVIDIA

NVIDIA

NXP Semiconductors

NXP Semiconductors

PathPartner Technology

PathPartner Technology

PathPartner Technology

PathPartner Technology

Qualcomm

Qualcomm

QuickPlay

QuickPlay

Renesas

Renesas

Renesas

Renesas

Samasource

Samasource

Sighthound

Sighthound

SKUR

SKUR

StradVision

StradVision

Synopsys

Synopsys

Tend

Tend

Thales Group

Thales Group

Universidad de Castilla-La Mancha

Universidad de Castilla-La Mancha

VeriSilicon

VeriSilicon

VeriSilicon

VeriSilicon

videantis

videantis

videantis

videantis

Xilinx

Xilinx

Xilinx

Xilinx

Xilinx

Xilinx

ZMicro

ZMicro

 

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