FASTER TREES: STRATEGIES FOR ACCELERATED TRAINING AND PREDICTION OF RANDOM FORESTS FOR CLASSIFICATION OF POLSAR IMAGES
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[1] Tin Kam Ho,et al. The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[2] Leo Breiman,et al. Big Random Forests: Classification and Regression Forests forLarge Data Sets , 2014 .
[3] Mandy Eberhart,et al. Decision Forests For Computer Vision And Medical Image Analysis , 2016 .
[4] Toby Sharp,et al. Implementing Decision Trees and Forests on a GPU , 2008, ECCV.
[5] Xiang Chen,et al. Willows: a memory efficient tree and forest construction package , 2009, BMC Bioinformatics.
[6] Christos-Savvas Bouganis,et al. Accelerating Random Forest training process using FPGA , 2013, 2013 23rd International Conference on Field programmable Logic and Applications.
[7] Henrik Boström. Concurrent Learning of Large-Scale Random Forests , 2011, SCAI.
[8] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[9] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[10] Andreas Ziegler,et al. On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data , 2010, Bioinform..
[11] Ronny Hänsch. Generic object categorization in PolSAR images - and beyond , 2014 .
[12] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[13] Andreas Ziegler,et al. ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R , 2015, 1508.04409.
[14] Vincent Lepetit,et al. Keypoint recognition using randomized trees , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] K. Hornik,et al. Unbiased Recursive Partitioning: A Conditional Inference Framework , 2006 .
[16] Andrew W. Fitzgibbon,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.
[17] Olaf Hellwich,et al. Skipping the real world: Classification of PolSAR images without explicit feature extraction , 2017 .