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We propose an Active Learning approach to training a segmentation classifier that exploits geometric priors to streamline the annotation process in 3D image volumes.
Random Walks on Graphs: A Survey
L. Lovász · 1993
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A Sequential Algorithm for Training Text Classifiers
D. Lewis and W. Gale · 1994
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Less is more: Active learning with support vector machines
G. Schohn and D. Cohn · 2000
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The Elements of Statistical Learning
T. Hastie, R. Tibshirani, and J. Friedman · 2001
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Interaction in the Segmentation of Medical Images : A Survey
S. D. Olabarriaga and A. W. M. Smeulders · 2001
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Support Vector Machine Active Learning with Applications to Text Classification
S. Tong and D. Koller · 2002
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Query By Committee Made Real
R. Gilad-Bachrach, A. Navot, and N. Tishby · 2005
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Random Walks for Image Segmentation
L. Grady · 2006
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Batch Mode Active Learning and its Application to Medical Image Classification
S. C. H. Hoi, R. Jin, J. Zhu, and M. R. Lyu · 2006
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Active Learning with Gaussian Processes for Object Categorization
A. Kapoor, K. Grauman, R. Urtasun, and T. Darrell · 2007
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Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification
B. Andres, U. Koethe, M. Helmstaedter, W. Denk, and F. Hamprecht · 2008
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Multiple-Instance Active Learning
B. Settles, M. Craven, and S. Ray · 2008
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Multi-Class Active Learning for Image Classification
A. Joshi, F. Porikli, and N. Papanikolopoulos · 2009
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A Literature Survey of Active Machine Learning in the Context of Natural Language Processing
F. Olsson · 2009
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The Pascal Visual Object Classes Challenge (VOC2010) Results, 2010
M. Everingham, C. W. L. Van Gool and, J. Winn, and A. Zisserman · 2010
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A High-Level 3D Visualization API for Java and ImageJ
B. Schmid, J. Schindelin, A. Cardona, M. Longair, and M. Heisenberg · 2010
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Active Learning Literature Survey
B. Settles · 2010
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Active Testing for Face Detection and Localization
R. Sznitman and B. Jedynak · 2010
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Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks with Learned Shape Features
A. Lucchi, K. Smith, R. Achanta, G. Knott, and P. Fua · 2012
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Abdominal CTA Image Analysis through Active Learning and Decision Random Forests: Aplication to AAA Segmentation
J. Maiora and M. G. na · 2012
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Active Learning for Semantic Segmentation with Expected Change
A. Vezhnevets, J. Buhmann, and V. Ferrari · 2012
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Supervised Feature Learning for Curvilinear Structure Segmentation
C. Becker, R. Rigamonti, V. Lepetit, and P. Fua · 2013
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A Convex Optimization Framework for Active Learning
E. Elhamifar, G. Sapiro, A. Yang, and S. S. Sasrty · 2013
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Combining Generative and Discriminative Models for Semantic Segmentation
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A Global Spatial Similarity Optimization Scheme to Track Large Numbers of Dendritic Spines in Time-Lapse Confocal Microscopy
Q. Li, Z. Deng, Y. Zhang, X. Zhou, U. V. Nagerl, and S. T. C. Wong · 2011
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From Theories to Queries : Active Learning in Practice
B. Settles · 2011
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Active learning for interactive 3D image segmentation
A. Top, G. Hamarneh, and R. Abugharbieh · 2011
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SLIC Superpixels Compared to State-Of-The-Art Superpixel Methods
R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Suesstrunk · 2012
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State of the Art Survey on MRI Brain Tumor Segmentation
N. Gordillo, E. Montseny, and P. Sobrevilla · 2013
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Active Visual Recognition with Expertise Estimation in Crowdsourcing
C. Long, G. Hua, and A. Kapoor · 2013
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Fast Object Detection with Entropy-Driven Evaluation
R. Sznitman, C. Becker, F. Fleuret, and P. Fua · 2013
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Uncertainty Estimation and Visualization in Probabilistic Segmentation
A. Al-Taie, H. H. K., and L. Linsen · 2014
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Microsoft COCO: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. Zitnick · 2014
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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
B. Menza, A. Jacas, et al · 2014
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