Book Image

Deep Learning for Computer Vision

By : Rajalingappaa Shanmugamani
Book Image

Deep Learning for Computer Vision

By: Rajalingappaa Shanmugamani

Overview of this book

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface

Training the MNIST model in TensorFlow


In this section, we will learn about the Modified National Institute of Standards and Technology (MNIST) database data and build a simple classification model. The objective of this section is to learn the general framework for deep learning and use TensorFlow for the same. First, we will build a perceptron or logistic regression model. Then, we will train a CNN to achieve better accuracy. We will also see how TensorBoard helps visualize the training process and understand the parameters. 

The MNIST datasets

The MNIST data has handwritten digits from 0–9 with 60,000 images for training and 10,000 images for testing. This database is widely used to try algorithms with minimum preprocessing. It's a good and compact database to learn machine learning algorithms. This is the most famous database for image classification problems. A few examples are shown here:

As can be seen in the preceding figure, there are 10 labels for these handwritten characters. The...