Probabilistic Graphical Models for Computer Vision.
  • Author : Qiang Ji
  • Release Date : 12 December 2019
  • Publisher : Academic Press
  • Genre : Computers
  • Pages : 294
  • ISBN 13 : 9780128034958

Probabilistic Graphical Models for Computer Vision. Book Summary

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. Discusses PGM theories and techniques with computer vision examples Focuses on well-established PGM theories that are accompanied by corresponding pseudocode for computer vision Includes an extensive list of references, online resources and a list of publicly available and commercial software Covers computer vision tasks, including feature extraction and image segmentation, object and facial recognition, human activity recognition, object tracking and 3D reconstruction

Probabilistic Graphical Models for Computer Vision

Probabilistic Graphical Models for Computer Vision

Author : Qiang Ji
Publisher : Academic Press
Genre : Computers
Total View : 5252 Views
File Size : 43,9 Mb
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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 ...

Probabilistic Graphical Models for Computer Vision

Probabilistic Graphical Models for Computer Vision

Author : Qiang Ji
Publisher : Academic Press
Genre : Uncategorized
Total View : 2995 Views
File Size : 51,8 Mb
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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 ...

Probabilistic Graphical Models

Probabilistic Graphical Models

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Publisher : Springer Nature
Genre : Computers
Total View : 2258 Views
File Size : 42,6 Mb
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This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, graphical models, and deep learning, as well as an even greater number of exercises. The book ...

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Publisher : MIT Press
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Total View : 1407 Views
File Size : 49,9 Mb
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Publisher : Packt Publishing Ltd
Genre : Computers
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File Size : 47,8 Mb
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Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python About This Book Gain in-depth knowledge of Probabilistic Graphical Models Model time-series problems using Dynamic Bayesian Networks A practical guide to help you apply PGMs to real-world problems Who This Book Is For If you ...

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A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for ...

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Author : Simon J. D. Prince
Publisher : Cambridge University Press
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A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms....

Learning Probabilistic Graphical Models in R

Learning Probabilistic Graphical Models in R

Author : David Bellot
Publisher : Packt Publishing Ltd
Genre : Computers
Total View : 4661 Views
File Size : 49,7 Mb
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Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the ...