Coverart for item
The Resource Decision forests for computer vision and medical image analysis, A. Criminisi, J. Shotton, editors, (electronic resource)

Decision forests for computer vision and medical image analysis, A. Criminisi, J. Shotton, editors, (electronic resource)

Label
Decision forests for computer vision and medical image analysis
Title
Decision forests for computer vision and medical image analysis
Statement of responsibility
A. Criminisi, J. Shotton, editors
Contributor
Subject
Language
eng
Summary
This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests
Member of
Cataloging source
EBLCP
Dewey number
511.52
Index
index present
LC call number
QA166.2
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1972-
http://library.link/vocab/relatedWorkOrContributorName
  • Criminisi, Antonio
  • Shotton, J.
  • ebrary, Inc
Series statement
Advances in computer vision and pattern recognition
http://library.link/vocab/subjectName
  • Decision trees
  • Computer vision
  • Image processing
  • Diagnostic imaging
Label
Decision forests for computer vision and medical image analysis, A. Criminisi, J. Shotton, editors, (electronic resource)
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
  • A. Criminisi, J. Shotton
  • Manifold Forests
  • A. Criminisi, J. Shotton
  • Semi-supervised Classification Forests
  • A. Criminisi, J. Shotton
  • Applications in Computer Vision and Medical Image Analysis
  • Keypoint Recognition Using Random Forests and Random Ferns
  • V. Lepetit, P. Fua
  • Extremely Randomized Trees and Random Subwindows for Image Classification, Annotation, and Retrieval
  • R. Marée, L. Wehenkel, P. Geurts
  • The Decision Forest Model
  • Class-Specific Hough Forests for Object Detection
  • J. Gall, V. Lempitsky
  • Hough-Based Tracking of Deformable Objects
  • M. Godec, P. M. Roth, H. Bischof
  • Efficient Human Pose Estimation from Single Depth Images
  • J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore
  • Anatomy Detection and Localization in 3D Medical Images
  • A. Criminisi, D. Robertson, O. Pauly, B. Glocker, E. Konukoglu, J. Shotton, D. Mateus
  • Semantic Texton Forests for Image Categorization and Segmentation
  • M. Johnson, J. Shotton, R. Cipolla
  • Introduction: The Abstract Forest Model
  • Semi-supervised Video Segmentation Using Decision Forests
  • V. Badrinarayanan, I. Budvytis, R. Cipolla
  • Classification Forests for Semantic Segmentation of Brain Lesions in Multi-channel MRI
  • E. Geremia, D. Zikic, O. Clatz, B. H. Menze, B. Glocker, E. Konukoglu, J. Shotton
  • Manifold Forests for Multi-modality Classification of Alzheimer's Disease
  • K. R. Gray, P. Aljabar, R. A. Heckemann, A. Hammers, D. Rueckert
  • Entanglement and Differentiable Information Gain Maximization
  • A. Montillo, J. Tu, J. Shotton, J. Winn, J. E. Iglesias, D. N. Metaxas, A. Criminisi
  • Decision Tree Fields: An Efficient Non-parametric Random Field Model for Image Labeling
  • S. Nowozin, C. Rother, S. Bagon, T. Sharp, B. Yao, P. Kohli
  • A. Criminisi, J. Shotton
  • Efficient Implementation of Decision Forests
  • J. Shotton, D. Robertson, T. Sharp
  • The Sherwood Software Library
  • D. Roberston, J. Shotton, T. Sharp
  • Conclusions
  • A. Criminisi, J. Shotton
  • Classification Forests
  • A. Criminisi, J. Shotton
  • Regression Forests
  • A. Criminisi, J. Shotton
  • Density Forests
Control code
ebr10655046
Dimensions
cm.
Dimensions
unknown
Extent
xix, 368 p
File format
unknown
Form of item
online
Isbn
9781447149293
Isbn Type
(electronic bk.)
Level of compression
unknown
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic reproduction.
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)827212143
Label
Decision forests for computer vision and medical image analysis, A. Criminisi, J. Shotton, editors, (electronic resource)
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Color
multicolored
Contents
  • A. Criminisi, J. Shotton
  • Manifold Forests
  • A. Criminisi, J. Shotton
  • Semi-supervised Classification Forests
  • A. Criminisi, J. Shotton
  • Applications in Computer Vision and Medical Image Analysis
  • Keypoint Recognition Using Random Forests and Random Ferns
  • V. Lepetit, P. Fua
  • Extremely Randomized Trees and Random Subwindows for Image Classification, Annotation, and Retrieval
  • R. Marée, L. Wehenkel, P. Geurts
  • The Decision Forest Model
  • Class-Specific Hough Forests for Object Detection
  • J. Gall, V. Lempitsky
  • Hough-Based Tracking of Deformable Objects
  • M. Godec, P. M. Roth, H. Bischof
  • Efficient Human Pose Estimation from Single Depth Images
  • J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore
  • Anatomy Detection and Localization in 3D Medical Images
  • A. Criminisi, D. Robertson, O. Pauly, B. Glocker, E. Konukoglu, J. Shotton, D. Mateus
  • Semantic Texton Forests for Image Categorization and Segmentation
  • M. Johnson, J. Shotton, R. Cipolla
  • Introduction: The Abstract Forest Model
  • Semi-supervised Video Segmentation Using Decision Forests
  • V. Badrinarayanan, I. Budvytis, R. Cipolla
  • Classification Forests for Semantic Segmentation of Brain Lesions in Multi-channel MRI
  • E. Geremia, D. Zikic, O. Clatz, B. H. Menze, B. Glocker, E. Konukoglu, J. Shotton
  • Manifold Forests for Multi-modality Classification of Alzheimer's Disease
  • K. R. Gray, P. Aljabar, R. A. Heckemann, A. Hammers, D. Rueckert
  • Entanglement and Differentiable Information Gain Maximization
  • A. Montillo, J. Tu, J. Shotton, J. Winn, J. E. Iglesias, D. N. Metaxas, A. Criminisi
  • Decision Tree Fields: An Efficient Non-parametric Random Field Model for Image Labeling
  • S. Nowozin, C. Rother, S. Bagon, T. Sharp, B. Yao, P. Kohli
  • A. Criminisi, J. Shotton
  • Efficient Implementation of Decision Forests
  • J. Shotton, D. Robertson, T. Sharp
  • The Sherwood Software Library
  • D. Roberston, J. Shotton, T. Sharp
  • Conclusions
  • A. Criminisi, J. Shotton
  • Classification Forests
  • A. Criminisi, J. Shotton
  • Regression Forests
  • A. Criminisi, J. Shotton
  • Density Forests
Control code
ebr10655046
Dimensions
cm.
Dimensions
unknown
Extent
xix, 368 p
File format
unknown
Form of item
online
Isbn
9781447149293
Isbn Type
(electronic bk.)
Level of compression
unknown
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic reproduction.
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)827212143

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