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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

You're reading from   Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA Effective techniques for processing complex image data in real time using GPUs

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789348293
Length 380 pages
Edition 1st Edition
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Author (1):
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Bhaumik Vaidya Bhaumik Vaidya
Author Profile Icon Bhaumik Vaidya
Bhaumik Vaidya
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Table of Contents (15) Chapters Close

Preface 1. Introducing CUDA and Getting Started with CUDA FREE CHAPTER 2. Parallel Programming using CUDA C 3. Threads, Synchronization, and Memory 4. Advanced Concepts in CUDA 5. Getting Started with OpenCV with CUDA Support 6. Basic Computer Vision Operations Using OpenCV and CUDA 7. Object Detection and Tracking Using OpenCV and CUDA 8. Introduction to the Jetson TX1 Development Board and Installing OpenCV on Jetson TX1 9. Deploying Computer Vision Applications on Jetson TX1 10. Getting Started with PyCUDA 11. Working with PyCUDA 12. Basic Computer Vision Applications Using PyCUDA 13. Assessments 14. Other Books You May Enjoy

Summary

This chapter introduced the Jetson TX1 Development Board for deploying computer vision and deep learning applications on embedded platforms. It is a small credit card-sized module, which can be used for computationally intensive applications. It has a better performance per power dissipation value than the latest i7 processors. It can be used in many domains where computer vision and deep learning is used for performance improvement and embedded deployment. Nvidia provides a development kit that houses this module along with other peripherals, which can be used for rapid prototyping of all applications. Nvidia also provides an SDK called JetPack, which is a collection of many software packages, such as OpenCV, CUDA, and Visionworks. This chapter described the process of installing JetPack on a Jetson TX1 in detail. The next chapter will describe the process of using OpenCV...

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