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020 a| 9781447149286 (alk. paper);

020 a| 1447149289 (alk. paper);

020 a| 9781447149293 (ebk.);

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050 00 a| TA1634b| .D43 2013;

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245 00 a| Decision forests for computer vision and medical image analysish| [electronic resource] /c| A. Criminisi, J. Shotton, editors.;

260 a| London ;a| New York :b| Springer,c| [2013];

300 a| xix, 368 pages :b| illustrations (chiefly color) ;c| 24 cm.;

490 1 a| Advances in computer vision and pattern recognition,x| 2191-6586;

504 a| Includes bibliographical references (pages 347-365) and index.;

505 00 t| The Decision Forest Model --t| Introduction: The Abstract Forest Model /r| A. Criminisi, J. Shotton --t| Classification Forests /r| A. Criminisi, J. Shotton --t| Regression Forests /r| A. Criminisi, J. Shotton --t| Density Forests /r| A. Criminisi, J. Shotton --t| Manifold Forests /r| A. Criminisi, J. Shotton --t| Semi-supervised Classification Forests /r| A. Criminisi, J. Shotton --t| Applications in Computer Vision and Medical Image Analysis --t| Keypoint Recognition Using Random Forests and Random Ferns /r| V. Lepetit, P. Fua --t| Extremely Randomized Trees and Random Subwindows for Image Classification, Annotation, and Retrieval /r| R. Marée, L. Wehenkel, P. Geurts --t| Class-Specific Hough Forests for Object Detection /r| J. Gall, V. Lempitsky --t| Hough-Based Tracking of Deformable Objects /r| M. Godec, P.M. Roth, H. Bischof --t| Efficient Human Pose Estimation from Single Depth Images /r| J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore --t| Anatomy Detection and Localization in 3D Medical Images /r| A. Criminisi, D. Robertson, O. Pauly, B. Glocker, E. Konukoglu, J. Shotton, D. Mateus --t| Semantic Texton Forests for Image Categorization and Segmentation /r| M. Johnson, J. Shotton, R. Cipolla --t| Semi-supervised Video Segmentation Using Decision Forests /r| V. Badrinarayanan, I. Budvytis, R. Cipolla --t| Classification Forests for Semantic Segmentation of Brain Lesions in Multi-channel MRI /r| E. Geremia, D. Zikic, O. Clatz, B.H. Menze, B. Glocker, E. Konukoglu, J. Shotton --t| Manifold Forests for Multi-modality Classification of Alzheimer's Disease /r| K.R. Gray, P. Aljabar, R.A. Heckemann, A. Hammers, D. Rueckert --t| Entanglement and Differentiable Information Gain Maximization /r| A. Montillo, J. Tu, J. Shotton, J. Winn, J.E. Iglesias, D.N. Metaxas, A. Criminisi --t| Decision Tree Fields: An Efficient Non-parametric Random Field Model for Image Labeling /r| S. Nowozin, C. Rother, S. Bagon, T. Sharp, B. Yao, P. Kohli --t| Efficient Implementation of Decision Forests /r| J. Shotton, D. Robertson, T. Sharp --t| The Sherwood Software Library /r| D. Roberston, J. Shotton, T. Sharp --t| Conclusions /r| A. Criminisi, J. Shotton.;

506 a| Available only to authorized users.;

520 a| 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.--c| Source other than Library of Congress.;

538 a| Mode of access: World Wide Web;

650 0 a| Decision trees.=| ^A295237;

650 0 a| Computer vision.=| ^A162076;

650 0 a| Image processingx| Digital techniques.=| ^A142170;

650 0 a| Diagnostic imagingx| Digital techniques.=| ^A292168;

650 7 a| Computer vision.2| fast0| (OCoLC)fst00872687;

650 7 a| Decision trees.2| fast0| (OCoLC)fst00889089;

650 7 a| Diagnostic imagingx| Digital techniques.2| fast0| (OCoLC)fst00892359;

650 7 a| Image processingx| Digital techniques.2| fast0| (OCoLC)fst00967508;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Criminisi, Antonio,d| 1972-?| UNAUTHORIZED;

700 1 a| Shotton, J.q| (Jamie)?| UNAUTHORIZED;

830 0 a| Advances in computer vision and pattern recognition.=| ^A1286515;

856 40 z| Full text available from Springer Nature - Springer Computer Science eBooks 2013 English Internationalu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Flink.springer.com%2F10.1007%2F978-1-4471-4929-3;

856 40 z| Full text available from Springer Booksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Flink.springer.com%2F10.1007%2F978-1-4471-4929-3;

947 a| (OCoLC)ocn842841944;

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949 a| CLICK ON WEB ADDRESSw| ASISh| HSL77;

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Decision forests for computer vision and medical image analysis / A. Criminisi, J. Shotton, editors.

Other author	Criminisi, Antonio, 1972-
Other author	Shotton, J. (Jamie)
Format	Electronic
Publication Info	London ; New York : Springer, [2013]
Description	xix, 368 pages : illustrations (chiefly color) ; 24 cm.
Supplemental Content	Full text available from Springer Nature - Springer Computer Science eBooks 2013 English International
Supplemental Content	Full text available from Springer Books
Subjects	Decision trees. Computer vision. Image processing--Digital techniques. Diagnostic imaging--Digital techniques.

Series	Advances in computer vision and pattern recognition, 2191-6586 Advances in computer vision and pattern recognition. ^A1286515
Contents	The Decision Forest Model -- Introduction: 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 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 -- 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.
Abstract	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.-- Source other than Library of Congress.
Bibliography note	Includes bibliographical references (pages 347-365) and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2013930423
ISBN	9781447149286 (alk. paper)
ISBN	1447149289 (alk. paper)
ISBN	9781447149293 (ebk.)

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	Electronic Resources	Online Content Full text available from Springer Nature - Springer Computer Science eBooks 2013 English International Full text available from Springer Nature - Springer Computer Science eBooks 2013 English International	✔ Available

Decision forests for computer vision and medical image analysis / A. Criminisi, J. Shotton, editors.

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