Название: Computer Vision: Applications of Visual AI and Image Processing
Автор: Pancham Shukla, Rajanikanth Aluvalu, Shilpa Gite, Uma Maheswari V.
Издательство: De Gruyter
Год: 2023
Страниц: 370
Язык: английский
Формат: pdf (true), epub
Размер: 15.9 MB

This book focuses on the latest developments in the fields of visual AI, image processing and computer vision. It shows research in basic techniques like image pre-processing, feature extraction, and enhancement, along with applications in biometrics, healthcare, neuroscience and forensics. The book highlights algorithms, processes, novel architectures and results underlying machine intelligence with detailed execution flow of models.

Artificial Intelligence (AI) has occupied almost all the fields of our lives nowadays by making machines work and think like humans. To build the ability to “see” the objects, identify scenes and act accordingly, machines should have “vision” ability. Computer Vision (CV) is considered as one of the most powerful yet challenging fields of AI. To provide visual interpretation and contextual understanding of the digital images and videos by the machines, CV and its applications are well adopted by all the domains. The state of the art of CV models are most useful for image and video analysis and prediction of various applications in real life. CV tackles all images and visual representation/interpretation-related problems using the machine’s cognitive abilities that are possible with the help of deep learning approaches. Hence, to make the readers aware about recent advances in CV image processing, this book was planned.

This book focuses on the details of such techniques and algorithms along with the interesting case studies in the industry and also in our day-to-day lives. Review articles are a part of this book which enlightens about agriculture and natural resources management using CV, image processing-related topics such as color constancy, hyperspectral imaging and also face recognition for dictionary reading. This book discusses latest developments in the fields of visual AI, image processing and CV. It provides state-of-the-art applications that highlight CV algorithms, processes, novel architectures and fascinating results underlying machine intelligence with detailed execution flow of models. It also demonstrates research in basic processes like image preprocessing, feature extraction, enhancement along with interesting applications in biometrics, healthcare and others.

Readers of this book will gain a thorough understanding of CV, image processing and aligned application domains. Not only UG/PG/PhD students but also CV researchers and industry professionals will be benefited by its contents. Anyone with a basic background in image processing will find this book easily readable and adaptable. Happy reading!

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