This book introduces you to Deep Learning and explains all the concepts required to understand the basic working, development, and tuning of a neural network using Pytorch.

Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.

The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.

This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book.

This book will touch the core of image processing, from concepts to code using Python.

This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004.

The only prerequisite for this book is that you should have a sound knowledge of Python programming.

This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field.

This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing.