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Practical Convolutional Neural Networks

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

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788392303
Length 218 pages
Edition 1st Edition
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Authors (3):
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Mohit Sewak Mohit Sewak
Author Profile Icon Mohit Sewak
Mohit Sewak
LinkedIn
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
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
LinkedIn
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).nCurrently, 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
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Pradeep Pujari
https://www.linkedin.com/in/ppujari/
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Table of Contents (11) Chapters Close

Preface 1. Deep Neural Networks – Overview 2. Introduction to Convolutional Neural Networks FREE CHAPTER 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 10. Other Books You May Enjoy

Popular CNN Model Architectures

In this chapter, will introduce the ImageNet image database and also cover the architectures of the following popular CNN models:

  • LeNet
  • AlexNet
  • VGG
  • GoogLeNet
  • ResNet 
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Authors (3)

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Profile icon Mohit Sewak
Mohit Sewak
LinkedIn icon
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
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See other products by Mohit Sewak
Profile icon Pradeep Pujari
Pradeep Pujari
https://www.linkedin.com/in/ppujari/
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See other products by Pradeep Pujari
Profile icon Karim
Karim
LinkedIn icon Github icon
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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