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Cameras-Everywhere

Computer Vision Solutions and Privacy-by-Design

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. These days cameras are ubiquitous – in our smart phones, our cars, homes, and around our cities. And opportunities for computer vision are endless, extending across robotics, retail, healthcare, transportation, and even sustainable agriculture. Computer vision offers […]

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“APIs for Accelerating Vision and Inferencing: Options and Trade-offs,” a Presentation from Khronos

Neil Trevett, President of the Khronos Group and Vice President at NVIDIA, presents the “APIs for Accelerating Vision and Inferencing: Options and Trade-offs” tutorial at the May 2018 Embedded Vision Summit. The landscape of SDKs, APIs and file formats for accelerating inferencing and vision applications continues to rapidly evolve. Low-level compute APIs, such as OpenCL,

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Synopsys EV6x SEP 1600x1338

Synopsys Introduces Industry’s First ASIL D Ready Embedded Vision Processor IP for ADAS Applications and Self-Driving Vehicles

DesignWare EV6x Processors with Safety Enhancement Package Accelerate ISO 26262 SoC-level Functional Safety Certifications for AI-enabled Automotive SoCs Highlights ASIL B, C, and D Ready DesignWare EV6x Embedded Vision Processors with Safety Enhancement Package integrate safety-critical hardware features while maintaining high performance and minimizing area and power ASIL D Ready ARC MetaWare EV Development Toolkit

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EVA180x100

“Computer Vision at the Edge and in the Cloud: Architectures, Algorithms, Processors, and Tools,” a Presentation from the Embedded Vision Alliance

On April 11, 2018, Embedded Vision Alliance founder Jeff Bier delivered the presentation “Computer Vision at the Edge and in the Cloud: Architectures, Algorithms, Processors, and Tools” to the Santa Clara Valley Chapter of the IEEE Signal Processing Society. Bier discussed the benefits and trade-offs of edge, cloud, and hybrid… “Computer Vision at the Edge

“Computer Vision at the Edge and in the Cloud: Architectures, Algorithms, Processors, and Tools,” a Presentation from the Embedded Vision Alliance Read More +

10373_Vision_Q6_DSP_Diagram

Cadence Boosts Vision and AI Performance with New Tensilica Vision Q6 DSP IP

SAN JOSE, Calif., April 11, 2018—Cadence Design Systems, Inc. (NASDAQ: CDNS) today announced the Cadence® Tensilica® Vision Q6 DSP, its latest DSP for embedded vision and AI built on a new, faster processor architecture. The fifth-generation Vision Q6 DSP offers 1.5X greater vision and AI performance than its predecessor, the Vision P6 DSP, and 1.25X

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Data Sets for Machine Learning Model Training

Deep learning and other machine learning techniques have rapidly become a transformative force in computer vision. Compared to conventional computer vision techniques, machine learning algorithms deliver 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,

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Implementing Vision with Deep Learning in Resource-constrained Designs

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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Mentor-ASB-Logo-Black-Hires

Mentor Embedded Linux Platform Supports New AMD EPYC Embedded and AMD Ryzen Embedded Processors

Mentor® Embedded Linux (MEL) platform supports AMD’s new EPYC™ Embedded 3000 and Ryzen™ Embedded V1000 processors based on high-performance x86 “Zen” architecture Targets industrial, medical, machine vision and learning, networking, and edge computing device applications, with superior performance and a suite of on-chip security features Mentor provides “out-of- the-box” embedded Linux support for hardware-accelerated applications

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Computer Vision in Surround View Applications

The ability to "stitch" together (offline or in real-time) multiple images taken simultaneously by multiple cameras and/or sequentially by a single camera, in both cases capturing varying viewpoints of a scene, is becoming an increasingly appealing (if not necessary) capability in an expanding variety of applications. High quality of results is a critical requirement, one

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