Author Description

Artificial intelligence (AI) has a wide range of applications and uses in various professions that will continue to be integrated into real-world operations. One capability of AI that has seen tremendous growth is the computer vision and recognition technology. This development allows computers to understand and label images and has become a highly applicable method in numerous fields. Analyzing the performance of this technology and researching its real-world implementations is vital for professionals, institutions, and researchers. Practical Applications and Use Cases of Computer Vision and Recognition Systems is a collection of innovative research on the methods and modern uses of recognition and machine vision technologies in the real world. While highlighting topics including autonomous vehicles, evolutionary algorithms, and deep learning, this book is ideally designed for developers, practitioners, students, researchers, programmers, policymakers, engineers, and academicians seeking research on modern practices of computer vision and recognition systems in a variety of fields.