Theory and Applications of Computer Vision

Computer vision is a field of AI that teaches computers to understand visuals. It uses theories from image processing, machine learning and neuroscience to create algorithms. These algorithms help machines extract information from images and videos, like recognizing objects or understanding scenes. In real-world applications, computer vision is used widely. It powers technologies such as facial recognition for security, autonomous vehicles for navigation and medical imaging for diagnostics. It also aids in manufacturing quality control, environmental monitoring through satellite imagery analysis and enhances augmented reality experiences. Recent advances in deep learning, especially with convolutional neural networks (CNNs) have greatly improved computer vision accuracy and capabilities. As research progresses, computer vision continues to evolve, promising even more innovations across various industries. This book elucidates the concepts and innovative models around prospective developments with respect to computer vision. The book aims to shed light on some of the unexplored aspects of artificial intelligence and the recent research in this field. The readers would gain knowledge that would broaden their perspective about computer science & information technology.