Provider

The listing below showcases the most recently published Embedded Vision Academy content associated with various Embedded Vision Alliance member companies. Reference the links on the right side of this page to access the full suite of embedded vision content, sorted by member company

8tree


	"The Evolution of Depth Sensing: From Exotic to Ubiquitous," a Presentation from 8tree Erik Klass of 8tree delivers a presentation at the Embedded Vision Alliance's September 2017 Vision Industry and Technology Forum.
	"Designing Vision Systems for Human Operators and Workflows: A Case Study," a Presentation from 8tree Arun Chhabra of 8tree delivers a Business Insights presentation at the May 2017 Embedded Vision Summit.

AImotive


	Data Sets for Machine Learning Model Training For machine learning to deliver its potential, it requires sufficient high quality training data, plus developer knowledge of how to use it.

Algolux


	Image Quality Analysis, Enhancement and Optimization Techniques for Computer Vision Differences between images intended for human viewing and for computer analysis factor into vision camera hardware and software design.

Allied Vision


	Beyond-visible Light Applications in Computer Vision Expanding the analysis range to encompass the infrared and/or ultraviolet spectrum can be of great benefit in a range of vision applications
	"A Multi-purpose Vision Processor for Embedded Systems," a Presentation from Allied Vision Michael Melle and Felix Nikolaus of Allied Vision deliver an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

AMD


	Computer Vision in Surround View Applications The ability to stitch together multiple images, capturing varying viewpoints of a scene, is becoming increasingly valuable in applications.
	"How Computer Vision Is Accelerating the Future of Virtual Reality," a Presentation from AMD Allen Rush of AMD delivers a business presentation at the May 2016 Embedded Vision Summit.

Analog Devices


	May 2014 Embedded Vision Summit Technical Presentation: "Multiple Uses of Pipelined Video Pre-Processor Hardware in Vision Applications," Rajesh Mahapatra, Analog Devices Rajesh Mahapatra of Analog Devices delivers a technical presentation at the May 2014 Embedded Vision Summit.
	Hot Chips Symposium Presentation Underscores Analog Devices' Commitment to Vision Applications Attendees of the 2012 HOT CHIPS symposium recently learned about Analog Devices’ new BF60x family of video and vision processors.

ARM


	"Computer Vision on ARM: Faster Ways to Optimize Software for Advanced Mobile Computing Platforms," a Presentation from ARM Roberto Mijat of ARM delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.
	"This Changes Everything — Why Computer Vision Will Be Everywhere," a Presentation from ARM Tim Ramsdale of ARM delivers a Business Insights presentation at the May 2017 Embedded Vision Summit.

Au-Zone Technologies


	Implementing Vision with Deep Learning in Resource-constrained Designs This article reviews deep learning implementation options such as heterogeneous processing, network quantization, and software optimizations
	"Implementing an Optimized CNN Traffic Sign Recognition Solution," a Presentation from NXP Semiconductors and Au-Zone Technologies Rafal Malewski of NXP and Sébastien Taylor of Au-Zone deliver a Technical Insights presentation at the May 2017 Embedded Vision Summit.

Basler


	Visual Intelligence Opportunities in Industry 4.0 With the emergence of the "smart factory," visual intelligence will further evolve and mature, as well as expand into new applications.
	"Time of Flight Sensors: How Do I Choose Them and How Do I Integrate Them?," a Presentation from Basler Mark Hebbel of Basler delivers a Fundamentals presentation at the May 2017 Embedded Vision Summit.

BDTI


	Data Sets for Machine Learning Model Training For machine learning to deliver its potential, it requires sufficient high quality training data, plus developer knowledge of how to use it.
	Implementing Vision with Deep Learning in Resource-constrained Designs This article reviews deep learning implementation options such as heterogeneous processing, network quantization, and software optimizations

Cadence


	"Techniques to Reduce Power Consumption in Embedded DNN Implementations," a Presentation from Cadence Samer Hijazi of Cadence delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.
	"Scalable Neural Network Processors for Embedded Applications," a Presentation from Cadence Pulin Desai of Cadence delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

CEVA


	"Fast Inference in Low Power Systems via CEVA's Deep Neural Network Solution," a Presentation from CEVA Yair Siegel of CEVA delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.
	"Video Stabilization Using Computer Vision: Techniques for Embedded Devices," a Presentation from CEVA Ben Weiss of CEVA delivers a technical presentation at the May 2016 Embedded Vision Summit.

Embedded Vision Alliance


	"A New Approach to Mass Transit Security," a Presentation from Lux Research Mark Bünger of Lux Research delivers a presentation at the March 2018 Vision Industry and Technology Forum.
	"Evaluating Early Stage Investment Opportunities in Camera-First Innovations," a Presentation from Shasta Ventures Jacob Mullins of Shasta Ventures delivers a presentation at the March 2018 Vision Industry and Technology Forum.

Imagination Technologies


	"Training CNNs for Efficient Inference," a Presentation from Imagination Technologies Paul Brasnett of Imagination Technologies delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.
	"Efficient Convolutional Neural Network Inference on Mobile GPUs," a Presentation from Imagination Technologies Paul Brasnett of Imagination Technologies delivers an enabling technologies presentation at the May 2016 Embedded Vision Summit.

iMerit


	Data Sets for Machine Learning Model Training For machine learning to deliver its potential, it requires sufficient high quality training data, plus developer knowledge of how to use it.

Infineon


	Vision Processing Opportunities in Virtual Reality VR systems are incorporating practical computer vision techniques both to improve the user experience and reduce system cost.

Intel


	"Designing Deep Neural Network Algorithms for Embedded Devices," a Presentation from Intel Minje Park of Intel delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.
	"How Intel’s Latest RealSense Technology Can Help Your Embedded Systems See, Navigate, and Understand the Real World," a Presentation from Intel Anders Grunnet-Jepsen of Intel delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

LUXOFT


	Data Sets for Machine Learning Model Training For machine learning to deliver its potential, it requires sufficient high quality training data, plus developer knowledge of how to use it.
	"Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail," a Presentation from Luxoft Alexey Rybakov of Luxoft delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.

MathWorks


	"How to Test and Validate an Automated Driving System," a Presentation from MathWorks Avinash Nehemiah of MathWorks delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.
	"Deep Learning and Vision Algorithm Development in MATLAB Targeting Embedded GPUs," a Presentation from MathWorks Avinash Nehemiah and Girish Venkataramani of MathWorks deliver an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

Mentor


	Fundamentals of coolSRAM-1T Memory IP Advanced memory technologies such as Mentor Graphics' coolSRAM-1T are valuable in embedded vision designs.

MVTec


	Visual Intelligence Opportunities in Industry 4.0 With the emergence of the "smart factory," visual intelligence will further evolve and mature, as well as expand into new applications.
	"Embedded Vision Made Smart: Introduction to the HALCON Embedded Machine Vision Library," a Presentation from MVTec Olaf Munkelt of MVTec delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

NVIDIA


	Vision Processing Opportunities in Drones Drones are a rapidly growing market for both consumer and commercial applications, and they increasingly leverage embedded vision technology
	"NVIDIA VisionWorks, a Toolkit for Computer Vision," a Presentation from NVIDIA Elif Albuz of NVIDIA delivers an enabling technologies presentation at the May 2016 Embedded Vision Summit.

NXP


	"Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles," a Presentation from NXP Semiconductors Ali Osman Ors of NXP Semiconductors delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.
	"Implementing an Optimized CNN Traffic Sign Recognition Solution," a Presentation from NXP Semiconductors and Au-Zone Technologies Rafal Malewski of NXP and Sébastien Taylor of Au-Zone deliver a Technical Insights presentation at the May 2017 Embedded Vision Summit.

ON Semiconductor


	Vision Processing Opportunities in Virtual Reality VR systems are incorporating practical computer vision techniques both to improve the user experience and reduce system cost.
	"Image Sensors for Vision: Foundations and Trends," a Presentation from ON Semiconductor Robin Jenkin of ON Semiconductor delivers a technical presentation at the May 2016 Embedded Vision Summit.

PathPartner Technology


	"Approaches for Vision-based Driver Monitoring," a Presentation from PathPartner Technology Jayachandra Dakala of PathPartner Technology delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.

PTC


	"What's Augmented? What's Reality?," a Presentation from PTC Jay Wright of PTC delivers a presentation at the September 2016 Embedded Vision Alliance Member Meeting.

Qualcomm


	"Always-on Vision Becomes a Reality," a Presentation from Qualcomm Research Evgeni Gousev of Qualcomm Research delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.
	"Computer Vision and Machine Learning at the Edge," a Presentation from Qualcomm Technologies Michael Mangan of Qualcomm Technologies delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

Synopsys


	Implementing Vision with Deep Learning in Resource-constrained Designs This article reviews deep learning implementation options such as heterogeneous processing, network quantization, and software optimizations
	Software Frameworks and Toolsets for Deep Learning-based Vision Processing Deep learning-based vision processing is an increasingly popular and robust alternative to classical computer vision algorithms.

Texas Instruments


	Stereo Vision: Facing the Challenges and Seeing the Opportunities for ADAS Applications The next engineering frontier, arguably the most challenging for the technology community, is real-time machine vision and intelligence.
	Cloud-versus-Edge and Centralized-versus-Distributed: Evaluating Vision Processing Alternatives Image processing can optionally take place within the edge device, in a network-connected cloud server, or subdivided among these locations.

Thundersoft


	"The Power of a Turnkey Camera Solution: Introduction to the Camera Development Kit", a Presentation from Thundersoft Fan Wang of Thundersoft delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

VeriSilicon


	OpenVX Enables Portable, Efficient Vision Software OpenVX enables embedded vision application software developers to efficiently harness the processing resources available in SoCs and systems

videantis


	Computer Vision in Surround View Applications The ability to stitch together multiple images, capturing varying viewpoints of a scene, is becoming increasingly valuable in applications.
	"Computer-vision-based 360-degree Video Systems: Architectures, Algorithms and Trade-offs," a Presentation from videantis Marco Jacobs of videantis delivers a Technical Insights presentation at the May 2017 Embedded Vision Summit.

Wave Computing


	"New Dataflow Architecture for Machine Learning," a Presentation from Wave Computing Chris Nicol of Wave Computing delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.
	"Enabling the Full Potential of Machine Learning," a Presentation from Wave Computing Derek Meyer of Wave Computing delivers a Business Insights presentation at the May 2017 Embedded Vision Summit.

Xilinx


	Visual Intelligence Opportunities in Industry 4.0 With the emergence of the "smart factory," visual intelligence will further evolve and mature, as well as expand into new applications.
	Software Frameworks and Toolsets for Deep Learning-based Vision Processing Deep learning-based vision processing is an increasingly popular and robust alternative to classical computer vision algorithms.

XIMEA


	"PCI Express – A High-bandwidth Interface for Multi-camera Embedded Systems," a Presentation from XIMEA Max Larin of XIMEA delivers an Enabling Technologies presentation at the May 2017 Embedded Vision Summit.

Search

Provider

Subscribe to the Embedded Vision Insights Newsletter