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Practical Computer Vision

You're reading from Practical Computer Vision

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788297684

Pages 234 pages

Edition 1st Edition

Languages

Concepts

Computer Vision

Author (1):

Abhinav Dadhich

Table of Contents (12) Chapters

Preface

1. A Fast Introduction to Computer Vision

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

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Datasets

In computer vision, datasets play a key role in developing efficient applications. Also, now, with the availability of large open source datasets, it has become much easier to create best performing models for computer vision tasks. In this section, we will see several datasets for computer vision.

ImageNet

ImageNet is one of the largest annotated datasets for computer vision. The data is arranged according to a hierarchical order. There are 1,000 classes with 1.4 million images overall. Though the images are for non-commercial use, ImageNet is still one of the most popular datasets when it comes to learning computer vision. Especially in deep learning, the dataset is used to create image classification models due...

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Authors (1)

Abhinav Dadhich

Abhinav Dadhich is a Researcher and Application Developer on deep learning at Abeja Inc. Tokyo. His day is often filled with designing deep learning models for computer vision applications like image classification, object detection, segmentation etc. His passion lies in understanding and replicating human vision system. Previously, he has worked on 3D mapping and robot navigation. He has graduated with B.Tech. in EE from IIT Jodhpur, India and has done his M.Eng. in Information Science from NAIST, Japan. He puts up notes and codes for several topics on GitHub profile.

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