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

Summary


In this chapter, we have understood the problems associated with image captions. We saw a few techniques involving natural language processing and various word2vec models such as GLOVE. We understood several algorithms such as CNN2RNN, metric learning, and combined objective. Later, we implemented a model that combines CNN and LSTM. 

In the next chapter, we will come to understand generative models. We will learn and implement style algorithms from scratch and cover a few of the best models. We will also cover the cool Generative Adversarial Networks (GAN) and its various applications.