{"id":416,"date":"2017-05-17T18:39:45","date_gmt":"2017-05-17T18:39:45","guid":{"rendered":"https:\/\/www.edge-ai-vision.com\/?page_id=416"},"modified":"2020-01-10T19:03:17","modified_gmt":"2020-01-10T19:03:17","slug":"may-2017-embedded-vision-summit-replay","status":"publish","type":"page","link":"https:\/\/www.edge-ai-vision.com\/the-summit\/may-2017-embedded-vision-summit-replay\/","title":{"rendered":"May 2017 Embedded Vision Summit Replay"},"content":{"rendered":"

Conference Presentation Slides<\/strong><\/h3>\n\n\n\n
\"\"<\/a><\/td>\n\n

2017 Embedded Vision Summit Slides<\/span>
\n\t\t\t(214 MB—click to download.)<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Conference Overview Presentations<\/strong><\/h3>\n\n\n\n\n
\"\"<\/a><\/td>\n\n

Welcome Remarks and Conference Overview (Day 1)<\/strong>
\n\t\t\tJeff Bier, Embedded Vision Alliance<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

Welcome Remarks and Conference Overview (Day 2)<\/strong>
\n\t\t\tJeff Bier, Embedded Vision Alliance<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Keynote Presentation<\/strong><\/h3>\n\n\n\n
\"\"<\/a><\/td>\n\n

"Deep Visual Understanding from Deep Learning"<\/strong>
\n\t\t\tProfessor Jitendra Malik, University of California, Berkeley<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Business Insights Track Presentations<\/strong><\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

"Video Cameras Without Video: Opportunities For Sensing With Embedded Vision"<\/strong>
\n\t\t\tMichael Tusch<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing Vision Systems for Human Operators and Workflows: A Case Study"<\/strong>
\n\t\t\tArun Chhabra, 8tree<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"This Changes Everything — Why Computer Vision Will Be Everywhere"<\/strong>
\n\t\t\tTim Ramsdale, ARM<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How 3D Maps Will Change the World"<\/strong>
\n\t\t\tVitaliy Goncharuk, Augmented Pixels<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Blending Cloud and Edge Machine Learning to Deliver Real-time Video Monitoring"<\/strong>
\n\t\t\tCarter Maslan, Camio<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Intelligent Video Surveillance: Are We There Yet?"<\/strong>
\n\t\t\tNik Gagvani, CheckVideo<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How to Start an Embedded Vision Company"<\/strong>
\n\t\t\tChris Rowen, Cognite Ventures<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"1,000X in Three Years: How Embedded Vision is Transitioning from Exotic to Everyday"<\/strong>
\n\t\t\tJeff Bier, Embedded Vision Alliance and BDTI<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The Rapid Evolution and Future of Machine Perception"<\/strong>
\n\t\t\tJay Yagnik, Google<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Vision for All?"<\/strong>
\n\t\t\tJeff McVeigh, Intel<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Using Markerless Motion Capture to Win Baseball Games"<\/strong>
\n\t\t\tSteven Cadavid, KinaTrax<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The Coming Shift from Image Sensors to Image Sensing"<\/strong>
\n\t\t\tPaul Gallagher, LG<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Automakers at a Crossroads: How Embedded Vision and Autonomy Will Reshape the Industry"<\/strong>
\n\t\t\tMark Bünger, Lux Research<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Another Set of Eyes: Machine Vision Automation Solutions for In Vitro Diagnostics"<\/strong>
\n\t\t\tSadie Zeller, Microscan Systems<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Using Satellites to Extract Insights on the Ground"<\/strong>
\n\t\t\tBoris Babenko, Orbital Insight<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Enabling the Full Potential of Machine Learning"<\/strong>
\n\t\t\tDerek Meyer, Wave Computing<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"What’s Hot? The M&A and Funding Landscape for Computer Vision Companies"<\/strong>
\n\t\t\tRandy Burger, Woodside Capital Partners<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

Vision Entrepreneurs' Panel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

Vision Tank Competition Finalist Presentations<\/strong>
\n\t\t\tAlways Innovating, Imagry, Lucid VR, Machines with Vision, and Perceptin<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Enabling Technologies Track Presentations<\/strong><\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

"A Multi-purpose Vision Processor for Embedded Systems"<\/strong>
\n\t\t\tMichael Melle and Felix Nikolaus, Allied Vision<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"A New Generation Vision Camera for Embedded Systems"<\/strong>
\n\t\t\tPaul Maria Zalewski, Allied Vision<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Computer Vision on ARM: The Spirit Object Detection Accelerator"<\/strong>
\n\t\t\tTim Hartley, ARM<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Computer Vision on ARM: Faster Ways to Optimize Software for Advanced Mobile Computing Platforms"<\/strong>
\n\t\t\tRoberto Mijat, ARM<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Scalable Neural Network Processors for Embedded Applications"<\/strong>
\n\t\t\tPulin Desai, Cadence<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Fast Inference in Low Power Systems via CEVA's Deep Neural Network Solution"<\/strong>
\n\t\t\tYair Siegel, CEVA<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Developing Real-time Video Applications with CoaXPress"<\/strong>
\n\t\t\tJean-Michel Wintgens, Euresys<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Ultra-Efficient VPU: Low-power Deep Learning, Computer Vision and Computational Photography"<\/strong>
\n\t\t\tPetronel Bigioi, FotoNation<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Implementing the TensorFlow Deep Learning Framework on Qualcomm’s Low-power DSP"<\/strong>
\n\t\t\tPete Warden, Google<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How Intel’s Latest RealSense Technology Can Help Your Embedded Systems See, Navigate, and Understand the Real World"<\/strong>
\n\t\t\tAnders Grunnet-Jepsen, Intel<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Deep Learning and Vision Algorithm Development in MATLAB Targeting Embedded GPUs"<\/strong>
\n\t\t\tAvinash Nehemiah and Girish Venkataramani, MathWorks<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Embedded Vision Made Smart: Introduction to the HALCON Embedded Machine Vision Library"<\/strong>
\n\t\t\tOlaf Munkelt, MVTec<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Always-on Vision Becomes a Reality"<\/strong>
\n\t\t\tEvgeni Gousev, Qualcomm Research<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Computer Vision and Machine Learning at the Edge"<\/strong>
\n\t\t\tMichael Mangan, Qualcomm Technologies<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing Scalable Embedded Vision SoCs from Day 1"<\/strong>
\n\t\t\tPierre Paulin, Synopsys<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The Power of a Turnkey Camera Solution: Introduction to the Camera Development Kit"<\/strong>
\n\t\t\tFan Wang, Thundersoft<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"New Dataflow Architecture for Machine Learning"<\/strong>
\n\t\t\tChris Nicol, Wave Computing<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Caffe to Zynq: State-of-the-Art Machine Learning Inference Performance in Less Than 5 Watts"<\/strong>
\n\t\t\tVinod Kathail, Xilinx<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"OpenCV on Zynq: Accelerating 4k60 Dense Optical Flow and Stereo Vision"<\/strong>
\n\t\t\tNick Ni, Xilinx<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"PCI Express – A High-bandwidth Interface for Multi-camera Embedded Systems"<\/strong>
\n\t\t\tMax Larin, XIMEA<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Fundamentals Track Presentations<\/strong><\/h3>\n\n\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

"Time of Flight Sensors: How Do I Choose Them and How Do I Integrate Them?"<\/strong>
\n\t\t\tMark Hebbel, Basler<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Demystifying Deep Neural Networks"<\/strong>
\n\t\t\tShehrzad Qureshi, BDTI<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How to Choose a 3D Vision Technology"<\/strong>
\n\t\t\tChris Osterwood, Carnegie Robotics<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"A Shallow Dive into Training Deep Neural Networks"<\/strong>
\n\t\t\tSammy Sidhu, DeepScale<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Introduction to Optics for Embedded Vision"<\/strong>
\n\t\t\tJessica Gehlhar, Edmund Optics<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Unsupervised Everything"<\/strong>
\n\t\t\tLuca Rigazio, Panasonic<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How CNNs Localize Objects with Increasing Precision and Speed"<\/strong>
\n\t\t\tAuro Tripathy, ShatterLine Labs<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Technical Insights Track Presentations<\/strong><\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

"Adventures in DIY Embedded Vision: The Can’t-miss Dartboard"<\/strong>
\n\t\t\tMark Rober<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing CNN Algorithms for Real-time Applications"<\/strong>
\n\t\t\tMatthew Chiu, Almond AI<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How Image Sensor and Video Compression Parameters Impact Vision Algorithms"<\/strong>
\n\t\t\tIlya Brailovskiy, Amazon Lab126<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Making Cozmo See"<\/strong>
\n\t\t\tAndrew Stein, Anki<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Techniques to Reduce Power Consumption in Embedded DNN Implementations"<\/strong>
\n\t\t\tSamer Hijazi, Cadence<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The OpenVX Computer Vision Library Standard for Portable, Efficient Code"<\/strong>
\n\t\t\tFrank Brill, Cadence and the Khronos Group<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing a Stereo IP Camera From Scratch"<\/strong>
\n\t\t\tAnton Leontiev, ELVEES, JSC<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Collaboratively Benchmarking and Optimizing Deep Learning Implementations"<\/strong>
\n\t\t\tUnmesh Bordoloi, General Motors<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Training CNNs for Efficient Inference"<\/strong>
\n\t\t\tPaul Brasnett, Imagination Technologies<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Edge Intelligence: Visual Reinforcement Learning for Mobile Devices"<\/strong>
\n\t\t\tAdham Ghazali, Imagry<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing a Wearable Imaging Device – for Mice"<\/strong>
\n\t\t\tShung Chieh, Inscopix<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing Deep Neural Network Algorithms for Embedded Devices"<\/strong>
\n\t\t\tMinje Park, Intel<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Making OpenCV Code Run Fast"<\/strong>
\n\t\t\tVadim Pisarevsky, Intel<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The Battle Between Traditional Algorithms and Deep Learning: The 3 Year Horizon"<\/strong>
\n\t\t\tCormic Brick, Intel (Movidius Group)<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"The Vision Acceleration API Landscape: Options and Trade-offs"<\/strong>
\n\t\t\tNeil Trevett, Khronos Group and NVIDIA<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail"<\/strong>
\n\t\t\tAlexey Rybakov, Luxoft<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Performing Multiple Perceptual Tasks With a Single Deep Neural Network"<\/strong>
\n\t\t\tAndrew Rabinovich, Magic Leap<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"How to Test and Validate an Automated Driving System"<\/strong>
\n\t\t\tAvinash Nehemiah, MathWorks<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing and Implementing Camera ISP Algorithms Using Deep Learning and Computer Vision"<\/strong>
\n\t\t\tVal Marchevsky, Motorola<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Implementing an Optimized CNN Traffic Sign Recognition Solution"<\/strong>
\n\t\t\tRafal Malewski, NXP Semiconductors
\n\t\t\tSébastien Taylor, Au-Zone Technologies<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles"<\/strong>
\n\t\t\tAli Osman Ors, NXP Semiconductors<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"A Fast Object Detector for ADAS using Deep Learning"<\/strong>
\n\t\t\tMinyoung Kim, Panasonic<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Approaches for Vision-based Driver Monitoring"<\/strong>
\n\t\t\tDakala Jayachandra, PathPartner Technology<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Designing a Vision-based, Solar-powered Rear Collision Warning System"<\/strong>
\n\t\t\tAman Sikka, Pearl Automation<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Vision Challenges in a Robotic Power Tool"<\/strong>
\n\t\t\tAlec Rivers, Shaper Tools<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Image Sensor Formats and Interfaces for IoT Applications"<\/strong>
\n\t\t\tTatsuya Sugioka, Sony<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Moving CNNs from Academic Theory to Embedded Reality"<\/strong>
\n\t\t\tTom Michiels, Synopsys<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"End to End Fire Detection Deep Neural Network Platform"<\/strong>
\n\t\t\tDivya Jain, Tyco Innovation<\/a><\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\n\n

"Computer-vision-based 360-degree Video Systems: Architectures, Algorithms and Trade-offs"<\/strong>
\n\t\t\tMarco Jacobs, videantis<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/a>Technology Showcase Demonstrations<\/strong><\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\"3M\"<\/a><\/td>\n\n

3M<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"AImotive\"<\/a><\/td>\n\n

AImotive<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Aldec\"<\/a><\/td>\n\n

Aldec<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Aldec\"<\/a><\/td>\n\n

Aldec<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Allied<\/a><\/td>\n\n

Allied Vision<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Allied<\/a><\/td>\n\n

Allied Vision<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Anki\"<\/a><\/td>\n\n

Anki<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"ARM\"<\/a><\/td>\n\n

ARM<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"ARM\"<\/a><\/td>\n\n

ARM<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"ARM\"<\/a><\/td>\n\n

ARM<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"ARM\"<\/a><\/td>\n\n

ARM<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Au-Zone<\/a><\/td>\n\n

Au-Zone Technologies<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Avnet\"<\/a><\/td>\n\n

Avnet<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"BDTI\"<\/a><\/td>\n\n

BDTI<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"BDTI\"<\/a><\/td>\n\n

BDTI<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"BDTI\"<\/a><\/td>\n\n

BDTI<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Cadence\"<\/a><\/td>\n\n

Cadence<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Cadence\"<\/a><\/td>\n\n

Cadence<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"CEVA\"<\/a><\/td>\n\n

CEVA<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"CEVA\"<\/a><\/td>\n\n

CEVA<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Imagination<\/a><\/td>\n\n

Imagination Technologies<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Imagination<\/a><\/td>\n\n

Imagination Technologies<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Intel\"<\/a><\/td>\n\n

Intel<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Lucid<\/a><\/td>\n\n

Lucid VR<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Luxoft\"<\/a><\/td>\n\n

Luxoft<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Luxoft\"<\/a><\/td>\n\n

Luxoft<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Machines<\/a><\/td>\n\n

Machines With Vision<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"NET\"<\/a><\/td>\n\n

NET<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Nextchip\"<\/a><\/td>\n\n

Nextchip<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Nextchip\"<\/a><\/td>\n\n

Nextchip<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"NXP<\/a><\/td>\n\n

NXP Semiconductors<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"NXP<\/a><\/td>\n\n

NXP Semiconductors<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Pearl<\/a><\/td>\n\n

Pearl Automation<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"PerceptIn\"<\/a><\/td>\n\n

PerceptIn<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Shaper<\/a><\/td>\n\n

Shaper Tools<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Synopsys\"<\/a><\/td>\n\n

Synopsys<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Synopsys\"<\/a><\/td>\n\n

Synopsys<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Thundersoft\"<\/a><\/td>\n\n

Thundersoft<\/strong><\/a><\/p>\n<\/td>\n<\/tr>\n

\"Xilinx\"<\/a><\/td>\n\n

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Conference Presentation Slides 2017 Embedded Vision Summit Slides (214 MB—click to download.) 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