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Practical Computer Vision

You're reading from   Practical Computer Vision Extract insightful information from images using TensorFlow, Keras, and OpenCV

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Length 234 pages
Edition 1st Edition
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Author (1):
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Abhinav Dadhich Abhinav Dadhich
Author Profile Icon Abhinav Dadhich
Abhinav Dadhich
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Table of Contents (12) Chapters Close

Preface 1. A Fast Introduction to Computer Vision FREE CHAPTER 2. Libraries, Development Platform, and Datasets 3. Image Filtering and Transformations in OpenCV 4. What is a Feature? 5. Convolutional Neural Networks 6. Feature-Based Object Detection 7. Segmentation and Tracking 8. 3D Computer Vision 9. Mathematics for Computer Vision 10. Machine Learning for Computer Vision 11. Other Books You May Enjoy

References

  • Sturm Jürgen, Nikolas Engelhard, Felix Endres, Wolfram Burgard, and Daniel Cremers. A Benchmark for the Evaluation of RGB-D SLAM Systems. In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, pp. 573-580. IEEE, 2012.
  • Mur-Artal Raul, Jose Maria Martinez Montiel, and Juan D. Tardos. ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics 31, no. 5 (2015): 1147-1163.
  • Rublee Ethan, Vincent Rabaud, Kurt Konolige, and Gary Bradski. ORB: an efficient alternative to SIFT or SURF. In Computer Vision (ICCV), 2011 IEEE international conference on, pp. 2564-2571. IEEE, 2011.
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