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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA
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Table of Contents

Table of Contents

  1. Introduction to CUDA and Getting Started with CUDA
  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 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 application using PyCUDA

About the Author

Bhaumik Vaidya is an experienced computer vision engineer and mentor. He has worked extensively on OpenCV Library in solving computer vision problems. He is a University gold medalist in masters and is now doing a PhD in the acceleration of computer vision algorithms built using OpenCV and deep learning libraries on GPUs. He has a background in teaching and has guided many projects in computer vision and VLSI(Very-large-scale integration). He has worked in the VLSI domain previously as an ASIC verification engineer, so he has very good knowledge of hardware architectures also. He has published many research papers in reputable journals to his credit. He, along with his PhD mentor, has also received an NVIDIA Jetson TX1 embedded development platform as a research grant from NVIDIA.

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