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Probabilistic Graphical Models for Computer Vision. Ji Hardback Academic Press

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Probabilistic Graphical Models for Computer Vision.

Helps readers solve their computer vision problems using Probabilistic Graphical Models

Qiang Ji (Author)

9780128034675

Hardback, published 13 December 2019

294 pages

23.5 x 19 x 2.3 cm, 0.77 kg

\""The book describes probabilistic graphical models in application to computer vision tasks. The theoretical concepts are accompanied by illustrative figures and algorithms in pseudocode. All the main categories of models are referred to. The applications range from image denoising and segmentation, object detection and tracking to 3D reconstruction and action recognition. It is a book that is valuable for theoreticians and practitioners alike.\"" --zbMath/European Mathematical Society and the Heidelberg Academy of Sciences and Humanities

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 ]

Probabilistic Graphical Models for Computer Vision. Ji Hardback Academic Press

Probabilistic Graphical Models for Computer Vision.

Helps readers solve their computer vision problems using Probabilistic Graphical Models

Qiang Ji (Author)

9780128034675

Hardback, published 13 December 2019

294 pages

23.5 x 19 x 2.3 cm, 0.77 kg

\""The book describes probabilistic graphical models in application to computer vision tasks. The theoretical concepts are accompanied by illustrative figures and algorithms in pseudocode. All the main categories of models are referred to. The applications range from image denoising and segmentation, object detection and tracking to 3D reconstruction and action recognition. It is a book that is valuable for theoreticians and practitioners alike.\"" --zbMath/European Mathematical Society and the Heidelberg Academy of Sciences and Humanities

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 ]

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