© 2018

Practical Computer Vision Applications Using Deep Learning with CNNs

With Detailed Examples in Python Using TensorFlow and Kivy


Table of contents

  1. Front Matter
    Pages i-xxii
  2. Ahmed Fawzy Gad
    Pages 1-44
  3. Ahmed Fawzy Gad
    Pages 45-106
  4. Ahmed Fawzy Gad
    Pages 107-128
  5. Ahmed Fawzy Gad
    Pages 129-181
  6. Ahmed Fawzy Gad
    Pages 183-227
  7. Ahmed Fawzy Gad
    Pages 229-294
  8. Ahmed Fawzy Gad
    Pages 295-338
  9. Ahmed Fawzy Gad
    Pages 339-380
  10. Back Matter
    Pages 381-405

About this book


Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. 

For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than fully connected networks. You will implement a CNN in Python to give you a full understanding of the model.

After consolidating the basics, you will use TensorFlow to build a practical image-recognition application and make the pre-trained models accessible over the Internet using Flask. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads.

This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. 

You will:
  • Understand how ANNs and CNNs work 
  • Create computer vision applications and CNNs from scratch using Python
  • Follow a deep learning project from conception to production using TensorFlow
  • Use NumPy with Kivy to build cross-platform data science applications


Deep Learning Computer Vision Python Machine Learning Neural Network Convolutional Neural Network Image Processing TensorFlow

Authors and affiliations

  1. 1.MenoufiaEgypt

About the authors

Ahmed Fawzy Gad is a teaching assistant at the Faculty of Computers and Information (FCI), Menoufia University, Egypt. He has done his MSc in Computer Science. Ahmed is interested in deep learning, machine learning, computer vision, and Python. He aims to add value to the data science community by sharing his writings and tutorials. He is the author of the book "Practical Computer Vision Applications Using Deep Learning with CNN's" published by Apress. 

Bibliographic information

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