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Synopsys

Computer Vision for Augmented Reality in Embedded Designs

Algorithms, Articles, Augmented Reality, Edge AI and Vision Alliance, NXP Semiconductors, Processors, Sensors, Software, Synopsys, Technical Articles, Tools, videantis /

Augmented reality (AR) and related technologies and products are becoming increasingly popular and prevalent, led by their adoption in smartphones, tablets and other mobile computing and communications devices. While developers of more deeply embedded platforms are also motivated to incorporate AR capabilities in their products, the comparative scarcity of processing, memory, storage, and networking resources […]

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“Designing Smarter, Safer Cars with Embedded Vision Using EV Processor Cores,” a Presentation from Synopsys

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Fergus Casey, R&D Director for ARC Processors at Synopsys, presents the “Designing Smarter, Safer Cars with Embedded Vision Using Synopsys EV Processor Cores” tutorial at the May 2018 Embedded Vision Summit. Consumers, the automotive industry and government regulators are requiring greater levels of automotive functional safety with each new generation of cars. Embedded vision, using

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“New Deep Learning Techniques for Embedded Systems,” a Presentation from Synopsys

Algorithms, Processors, Software, Summit 2018, Synopsys, Tools, Videos /

Tom Michiels, System Architect for Embedded Vision at Synopsys, presents the “New Deep Learning Techniques for Embedded Systems” tutorial at the May 2018 Embedded Vision Summit. In the past few years, the application domain of deep learning has rapidly expanded. Constant innovation has improved the accuracy and speed of learning and inference. Many techniques are

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Implementing Vision with Deep Learning in Resource-constrained Designs

Algorithms, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, Processors, Software, Synopsys, Technical Articles, Tools /

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

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Implementing High-performance Deep Learning Without Breaking Your Power Budget

Articles, Synopsys, Technical Articles /

This article was originally published at Synopsys' website. It is reprinted here with the permission of Synopsys. Examples of applications abound where high-performance, low-power embedded vision processors are used: a mobile phone using face recognition to identify a user, an augmented or mixed reality headset identifying your hands and the layout of your living room

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The Evolution of Deep Learning for ADAS Applications

Articles, Synopsys, Technical Articles /

This technical article was originally published at Synopsys' website. It is reprinted here with the permission of Synopsys. Embedded vision solutions will be a key enabler for making automobiles fully autonomous. Giving an automobile a set of eyes – in the form of multiple cameras and image sensors – is a first step, but it

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Software Frameworks and Toolsets for Deep Learning-based Vision Processing

Algorithms, AMD, Articles, Au-Zone Technologies, BDTI, Edge AI and Vision Alliance, MVTec, Processors, Software, Synopsys, Technical Articles, Tools /

This article provides both background and implementation-detailed information on software frameworks and toolsets for deep learning-based vision processing, an increasingly popular and robust alternative to classical computer vision algorithms. It covers the leading available software framework options, the root reasons for their abundance, and guidelines for selecting an optimal approach among the candidates for a

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“Designing Scalable Embedded Vision SoCs from Day 1,” a Presentation from Synopsys

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Pierre Paulin, Director of R&D for Embedded Vision at Synopsys, presents the "Designing Scalable Embedded Vision SoCs from Day 1" tutorial at the May 2017 Embedded Vision Summit. Some of the most critical embedded vision design decisions are made early on and affect the design’s ultimate scalability. Will the processor architecture support the needed vision

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“Moving CNNs from Academic Theory to Embedded Reality,” a Presentation from Synopsys

Algorithms, Automotive, Processors, Software, Synopsys, Tools, Videos /

Tom Michiels, System Architect for Embedded Vision Processors at Synopsys, presents the "Moving CNNs from Academic Theory to Embedded Reality" tutorial at the May 2017 Embedded Vision Summit. In this presentation, you will learn to recognize and avoid the pitfalls of moving from an academic CNN/deep learning graph to a commercial embedded vision design. You

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Facial Analysis Delivers Diverse Vision Processing Capabilities

Algorithms, Articles, Automotive, Edge AI and Vision Alliance, Entertainment, Face Detection, Face Recognition, Medical, NXP Semiconductors, Processors, Retail, Security, Sensors, Software, Synopsys, Technical Articles, Tools, Xperi /

Computers can learn a lot about a person from their face – even if they don’t uniquely identify that person. Assessments of age range, gender, ethnicity, gaze direction, attention span, emotional state and other attributes are all now possible at real-time speeds, via advanced algorithms running on cost-effective hardware. This article provides an overview of

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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