Название: Probabilistic Graphical Models for Computer Vision Автор: Qiang Ji Издательство: Academic Press Серия: Computer Vision and Pattern Recognition Год: 2020 Страниц: 294 Язык: английский Формат: pdf (true), djvu Размер: 10.1 MB
Probabilistic Graphical Models for Computer Vision introduces probabilistic graphical models (PGMs) for computer vision problems and teaches how to develop the PGM model from training data. This book discusses PGMs and their significance in the context of solving computer vision problems, giving the basic concepts, definitions and properties. It also provides a comprehensive introduction to well-established theories for different types of PGMs, including both directed and undirected PGMs, such as Bayesian Networks, Markov Networks and their variants.
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