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Practical Convolutional Neural Networks

You're reading from Practical Convolutional Neural Networks Implement advanced deep learning models using Python

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781788392303

Length 218 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (3):

Mohit Sewak

Md. Rezaul Karim

Pradeep Pujari

View More author details

Table of Contents (16) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Deep Neural Networks – Overview FREE CHAPTER

2. Introduction to Convolutional Neural Networks

3. Build Your First CNN and Performance Optimization

4. Popular CNN Model Architectures

5. Transfer Learning

6. Autoencoders for CNN

7. Object Detection and Instance Segmentation with CNN

8. GAN: Generating New Images with CNN

9. Attention Mechanism for CNN and Visual Models

1. Other Books You May Enjoy

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Index

References

Paul Viola and Michael Jones, Rapid object detection using a boosted cascade of simple features, Conference on Computer Vision and Pattern Recognition, 2001.
Paul Viola and Michael Jones, Robust Real-time object detection, International Journal of Computer Vision, 2001.
Itseez2015opencv, OpenCV, Open Source Computer Vision Library, Itseez, 2015.
Ross B. Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, CoRR, arXiv:1311.2524, 2013.
Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, Computer Vision and Pattern Recognition, 2014.
M. Everingham, L. VanGool, C. K. I. Williams, J. Winn, A. Zisserman, The PASCAL Visual Object Classes Challenge 2012, VOC2012, Results.
D. Lowe. Distinctive image features from scale-invariant keypoints, IJCV, 2004.
N. Dalal and B. Triggs. Histograms of oriented gradients for human detection...

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Authors (3)

Mohit Sewak

Mohit Sewak

Mohit is a Python programmer with a keen interest in the field of information security. He has completed his Bachelor's degree in technology in computer science from Kurukshetra University, Kurukshetra, and a Master's in engineering (2012) in computer science from Thapar University, Patiala. He is a CEH, ECSA from EC-Council USA. He has worked in IBM, Teramatrix (Startup), and Sapient. He currently doing a Ph.D. from Thapar Institute of Engineering & Technology under Dr. Maninder Singh. He has published several articles in national and international magazines. He is the author of Python Penetration Testing Essentials, Python: Penetration Testing for Developers and Learn Python in 7 days, also by Packt. For more details on the author, you can check the following user name mohitraj.cs

See other products by Mohit Sewak

Karim

Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

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Pradeep Pujari

Pradeep Pujari

https://www.linkedin.com/in/ppujari/

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