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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 2. Parallel Programming using CUDA C FREE CHAPTER 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

Chapter 1

  1. The three options to increase the performance are as follows:
    • Having faster clock speed
    • More work per clock cycle by a single processor
    • Many small processors that can work in parallel. This option is used by GPU to improve performance.
  2. True
  3. CPUs are designed to improve latency and GPUs are designed to improve Throughput.
  4. The car will take 4 hours to reach the destination but it can only accommodate 5 persons, while the bus that can accommodate 40 persons takes 6 hours to reach the destination. The bus can transport 6.66 persons per hour, while the car can transport 1.2 persons per hour. Thus, car has better latency, and bus has better throughput.
  5. Image is nothing but a two dimensional array. Most of the computer vision applications involve processing of these two-dimensional arrays. It involves similar operations on a large amount of data, which can be efficiently...
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