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Medientyp:
Buch
Titel:
Decision forests for computer vision and medical image analysis
Enthält:
The Decision Forest ModelIntroduction: The Abstract Forest Model
/ A. Criminisi, J. Shotton
Classification Forests
/ A. Criminisi, J. Shotton
Regression Forests
/ A. Criminisi, J. Shotton
Density Forests
/ 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 AnalysisKeypoint 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
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
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
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.
Anmerkungen:
Literaturverz. S. 347 - 365 und Index
Beschreibung:
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.--