Название: Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python Автор: Joseph Awange, Bala Palancz
Издательство: Springer
Год: 2019 (2020 Edition)
Страниц: 419
Язык: английский
Формат: pdf (true)
Размер: 20.3 MB
The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks generalized by up-to-date points of view. Associated algorithms are deposited on iCloud.
Computer vision is a subfield of artificial intelligence that enables the understanding of the content of digital images, such as photographs. Currently, machine learning is making impressive inroads in tackling challenges posed by computer vision related tasks, promising further impressive advances.
Speaking of computer vision, two modes of books frequently appear (i) reference-based textbooks written by experts, who often are academics, targeting students and practitioners, and (ii), programming oriented books (i.e., play books) written by experts, who often are developers and engineers, and designed to be used as references by practitioners. Whereas the former mainly focus on general methods and theory (Maths) and not on the practical aspects of the problems and the applications of methods (code), the latter focuses mainly on the techniques and practical concerns of the problem solving, where the focus is placed on examples of codes and standard libraries.
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