| 000 | 01083camuu2200301 a 4500 | |
| 001 | 000045812983 | |
| 005 | 20141014134045 | |
| 008 | 130730s2013 enka 001 0 eng | |
| 020 | ▼a 9781447149286 (hbk.) | |
| 020 | ▼a 1447149289 (hbk.) | |
| 020 | ▼z 9781447149293 (eBook) | |
| 035 | ▼a (KERIS)BIB000013243017 | |
| 040 | ▼a 241048 ▼d 244002 | |
| 082 | 0 0 | ▼a 006.37 ▼2 23 |
| 084 | ▼a 006.37 ▼2 DDCK | |
| 090 | ▼a 006.37 ▼b D294 | |
| 245 | 0 0 | ▼a Decision forests for computer vision and medical image analysis / ▼c A. Criminisi, J. Shotton, editors. |
| 260 | ▼a London : ▼b Springer, ▼c 2013. | |
| 300 | ▼a xix, 368 p. : ▼b ill. ; ▼c 24 cm. | |
| 490 | 0 | ▼a Advances in computer vision and pattern recognition, ▼x 2191-6586 |
| 500 | ▼a "ISSN 2191-6594 (electronic)" -- title page verso. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Computer vision. |
| 650 | 0 | ▼a Computer vision in medicine. |
| 650 | 0 | ▼a Decision making ▼x Data processing. |
| 700 | 1 | ▼a Criminisi, Antonio, ▼d 1972-. |
| 700 | 1 | ▼a Shotton, J. ▼q (Jamie), |
Holdings Information
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|---|---|---|---|---|---|---|---|
| No. 1 | Location Sejong Academic Information Center/Course Reserves/ | Call Number 컴퓨터정보학과 006.37 D294 | Accession No. 151322587 | Availability Loan can not(reference room) | Due Date | Make a Reservation | Service |
| No. 2 | Location Sejong Academic Information Center/Course Reserves/ | Call Number 컴퓨터정보학과 006.37 D294 | Accession No. 151322588 | Availability Loan can not(reference room) | Due Date | Make a Reservation | Service |
Contents information
Author Introduction
A. Criminisi(엮은이)
J. Shotton(엮은이)
Table of Contents
Overview and Scope Notation and Terminology Part I: The Decision Forest Model Introduction: The Abstract Forest Model Classification Forests Regression Forests Density Forests Manifold Forests Semi-Supervised Classification Forests Part II: Applications in Computer Vision and Medical Image Analysis Keypoint Recognition Using Random Forests and Random Ferns V. Lepetit and P. Fua Extremely Randomized Trees and Random Subwindows for Image Classification, Annotation, and Retrieval R. Maree, L. Wehenkel and P. Geurts Class-Specific Hough Forests for Object Detection J. Gall and V. Lempitsky Hough-Based Tracking of Deformable Objects M. Godec, P. M. Roth and H. Bischof Efficient Human Pose Estimation from Single Depth Images J. Shotton, R. Girshick, A. Fitzgibbon, T. Sharp, M. Cook, M. Finocchio, R. Moore, P. Kohli, A. Criminisi, A. Kipman and A. Blake Anatomy Detection and Localization in 3D Medical Images A. Criminisi, D. Robertson, O. Pauly, B. Glocker, E. Konukoglu, J. Shotton, D. Mateus, A. Martinez Moller, S. G. Nekolla and N. Navab Semantic Texton Forests for Image Categorization and Segmentation M. Johnson, J. Shotton and R. Cipolla Semi-Supervised Video Segmentation Using Decision Forests V. Badrinarayanan, I. Budvytis and 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, O. M. Thomas, S. J. Price, T. Das, R. Jena, N. Ayache and A. Criminisi Manifold Forests for Multi-Modality Classification of Alzheimer's Disease K. R. Gray, P. Aljabar, R. A. Heckemann, A. Hammers and D. Rueckert Entangled Forests and Differentiable Information Gain Maximization A. Montillo, J. Tu, J. Shotton, J. Winn, J. E. Iglesias, D. N. Metaxas, and 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 and P. Kohli Part III: Implementation and Conclusion Efficient Implementation of Decision Forests J. Shotton, D. Robertson and T. Sharp The Sherwood Software Library D. Robertson, J. Shotton and T. Sharp Conclusions
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