Computer vision is one of the most widely studied sub-fields of computer science. It has several important applications, such as face detection, image searching, and artistic image conversion. With the popularity of deep learning methods, many recent applications of computer vision are in self-driving cars, robotics, medicine, Virtual reality, and Augmented reality. In this book, a practical approach of learning computer vision is shown. Using code blocks as well as a theoretical understanding of algorithms will help in building stronger computer vision fundamentals. This book teaches you how to create applications using standard tools such as OpenCV, Keras, and TensorFlow. The various concepts and implementations explained in this book can be used across several domains, such as robotics, image editing apps, and self-driving cars. In this book, each chapter is explained with accompanying code and results to enforce the learning together.
United States
United Kingdom
India
Germany
France
Canada
Russia
Spain
Brazil
Australia
Argentina
Austria
Belgium
Bulgaria
Chile
Colombia
Cyprus
Czechia
Denmark
Ecuador
Egypt
Estonia
Finland
Greece
Hungary
Indonesia
Ireland
Italy
Japan
Latvia
Lithuania
Luxembourg
Malaysia
Malta
Mexico
Netherlands
New Zealand
Norway
Philippines
Poland
Portugal
Romania
Singapore
Slovakia
Slovenia
South Africa
South Korea
Sweden
Switzerland
Taiwan
Thailand
Turkey
Ukraine