NVIDIA

www.nvidia.com

NVIDIA invented the highly parallel graphics processing unit—the GPU—in 1999. Since then, NVIDIA has set new standards in visual computing with interactive graphics on products ranging from smart phones and tablets to supercomputers and automobiles. Since computer vision is extremely computationally intensive, it is perfectly suited for parallel processing, and NVIDIA GPUs have led the way in the acceleration of computer vision applications. In embedded vision, NVIDIA is focused on delivering solutions for consumer electronics, driver assistance systems, and national defense programs. NVIDIA expertise in visual computing, combined with the power of NVIDIA parallel processors, delivers exceptional results.

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Rapid Prototyping on NVIDIA Jetson Platforms with MATLAB

This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. This article discusses how an application developer can prototype and deploy deep learning algorithms on hardware like the NVIDIA Jetson Nano Developer Kit with MATLAB. In previous posts, we explored how you can design and train deep learning …

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Speeding Up Semantic Segmentation Using MATLAB Container from NVIDIA NGC

This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Gone are the days of using a single GPU to train a deep learning model.  With computationally intensive algorithms such as semantic segmentation, a single GPU can take days to optimize a model. But multi-GPU hardware is expensive, …

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Using Calibration to Translate Video Data to the Real World

This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. DeepStream SDK 3.0 is about seeing beyond pixels. DeepStream exists to make it easier for you to go from raw video data to metadata that can be analyzed for actionable insights. Calibration is a key step in this …

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Using MATLAB and TensorRT on NVIDIA GPUs

This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. As we design deep learning networks, how can we quickly prototype the complete algorithm—including pre- and postprocessing logic around deep neural networks (DNNs) —to get a sense of timing and performance on standalone GPUs? This question comes up …

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Vision Processing Opportunities in Drones

UAVs (unmanned aerial vehicles), commonly known as drones, are a rapidly growing market and increasingly leverage embedded vision technology for digital video stabilization, autonomous navigation, and terrain analysis, among other functions. This article reviews drone market sizes and trends, and then discusses embedded vision technology applications in drones, such as image quality optimization, autonomous navigation, …

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“NVIDIA VisionWorks, a Toolkit for Computer Vision,” a Presentation from NVIDIA

Elif Albuz, Technical Lead for the VisionWorks Toolkit at NVIDIA, presents the "NVIDIA VisionWorks, a Toolkit for Computer Vision" tutorial at the May 2016 Embedded Vision Summit. In this talk, Albuz introduces the NVIDIA VisionWorks toolkit, a software development package for computer vision and image processing. VisionWorks implements and extends the Khronos OpenVX standard, and …

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“Computational Photography: Understanding and Expanding the Capabilities of Standard Cameras,” a Presentation from NVIDIA

Orazio Gallo, Senior Research Scientist at NVIDIA, presents the "Computational Photography: Understanding and Expanding the Capabilities of Standard Cameras" tutorial at the May 2016 Embedded Vision Summit. Today's digital cameras, even at the entry-level, produce pictures with quality comparable to that of high-end cameras of a decade ago. Image processing and computational photography algorithms play …

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OpenCL Eases Development of Computer Vision Software for Heterogeneous Processors

OpenCL™, a maturing set of programming languages and APIs from the Khronos Group, enables software developers to efficiently harness the profusion of diverse processing resources in modern SoCs, in an abundance of applications including embedded vision. Computer scientists describe computer vision, the use of digital processing and intelligent algorithms to interpret meaning from still and …

OpenCL Eases Development of Computer Vision Software for Heterogeneous Processors Read More +

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OpenCL Eases Development of Computer Vision Software for Heterogeneous Processors

OpenCL™, a maturing set of programming languages and APIs from the Khronos Group, enables software developers to efficiently harness the profusion of diverse processing resources in modern SoCs, in an abundance of applications including embedded vision. Computer scientists describe computer vision, the use of digital processing and intelligent algorithms to interpret meaning from still and …

OpenCL Eases Development of Computer Vision Software for Heterogeneous Processors Read More +

“An Update on OpenVX and Other Vision-Related Standards,” A Presentation from Khronos

Elif Albuz, Manager of Vision Software at NVIDIA, delivers the presentation "Update on OpenVX and Other Khronos Standards" at the December 2014 Embedded Vision Alliance Member Meeting. Elif provides an update on the newly released OpenVX standard, and other vision-related standards in progress.

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Accelerate Machine Learning with the cuDNN Deep Neural Network Library

This article was originally published at NVIDIA's developer blog. It is reprinted here with the permission of NVIDIA. By Larry Brown Solution Architect, NVIDIA Machine Learning (ML) has its origins in the field of Artificial Intelligence, which started out decades ago with the lofty goals of creating a computer that could do any work a …

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GPUTech

Embedded Vision: Enabling Smarter Mobile Apps and Devices

For decades, computer vision technology was found mainly in university laboratories and a few niche applications. Today, virtually every tablet and smartphone is capable of sophisticated vision functions such as hand gesture recognition, face recognition, gaze tracking, and object recognition. These capabilities are being used to enable new types of applications, user interfaces, and use …

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GPUTech

Introduction to OpenCV for Tegra

Do you want to write your own blazing fast, interactive mobile apps using computer vision technology? Apps that can make your camera smarter, find people's faces, understand their gestures, interpret scenes and augment them with graphics? The Tegra super chip and the OpenCV for Tegra library can help you to do just that! OpenCV for …

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GPUTech

Real-Time Traffic Sign Recognition on Mobile Processors

There is a growing need for fast and power-efficient computer vision on embedded devices. This session will focus on computer vision capabilities on embedded platforms available to ADAS developers, covering the OpenCV CUDA implementation and the new computer vision standard, OpenVX. In addition, Itseez traffic sign detection will be showcased. The algorithm is capable of …

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GPUTech

Getting Started With GPU-Accelerated Computer Vision Using OpenCV and CUDA

OpenCV is a free library for research and commercial purposes that includes hundreds of optimized computer vision and image processing algorithms. NVIDIA and Itseez have optimized many OpenCV functions using CUDA on desktop machines equipped with NVIDIA GPUs. These functions are 5 to 100 times faster in wall-clock time compared to their CPU counterparts. Anatoly …

Getting Started With GPU-Accelerated Computer Vision Using OpenCV and CUDA Read More +

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May 18 - 21, Santa Clara, California

The preeminent event for practical, deployable computer vision and visual AI, for product creators who want to bring visual intelligence to products.

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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