Название: Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer VisionАвтор: Karm Veer Arya, Ciro Rodriguez Rodriguez, Saurabh Singh
Издательство: Apple Academic Press/CRC Press
Год: 2024
Страниц: 341
Язык: английский
Формат: pdf (true)
Размер: 17.2 MB
This new volume provides in-depth and detailed knowledge about the latest research in image processing and Computer Vision techniques. Explaining the Machine Learning algorithms and models involved, the authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods.
The authors discuss Machine Learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using Deep Learning, using Machine Learning to record the climate changes in over time with remote sensing, and more.
Machine Learning (ML) algorithms learn from data by building adaptive mathematical models which can detect the pattern in the training data. One of the applications of Machine Learning is image processing and Computer Vision. Image processing (IP) is the manipulation of an image to process, analyze, and obtain the information provided for human interpretation. The interpretation of images by Machine Learning algorithms is the same as is done by our brains.
ML algorithms typically have steps to learn from data which include data preparation, data extraction, training the model, and making predictions by testing the model. High-quality data are the primary requirement of ML algorithms for fair level of predictions.
This book is a road map for the improvement of Computer Vision and IP field. The book will play a significant role in providing information about the ML algorithms and models used in IP and Computer Vision to new researchers and practitioners who wish to start working in this field. They would be able to differentiate between the various algorithms available and which would get the most precise result for a specific task involving certain constraints. This book will be useful because it will provide a vast amount of information and clarification on topics researched by a number of professionals working in the field. The researchers will come across the future scope of these technologies and get to know about the potential application of the same in solving real-life problems.
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