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LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs.

, , and . Pattern Recognit., 45 (9): 3544-3556 (2012)

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Dynamic Selection of Ensembles of Classifiers Using Contextual Information., , and . MCS, volume 5997 of Lecture Notes in Computer Science, page 145-154. Springer, (2010)LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs., , and . Pattern Recognit., 45 (9): 3544-3556 (2012)Multi-scale Forest Species Recognition Systems for Reduced Cost., , and . CoRR, (2017)Dynamic selection approaches for multiple classifier systems., , and . Neural Comput. Appl., 22 (3-4): 673-688 (2013)A multiple feature vector framework for forest species recognition., , , and . SAC, page 16-20. ACM, (2013)Inspeção Automática de Defeitos em Madeiras de Pinus usando Visão Computacional., , , and . RITA, 15 (2): 218- (2008)Leave-One-Out-Training and Leave-One-Out-Testing Hidden Markov Models for a Handwritten Numeral Recognizer: The Implications of a Single Classifier and Multiple Classifications., , , and . IEEE Trans. Pattern Anal. Mach. Intell., 31 (12): 2168-2178 (2009)An implicit segmentation-based method for recognition of handwritten strings of characters., , , , and . SAC, page 836-840. ACM, (2006)Large-Scale Multi-agent-Based Modeling and Simulation of Microblogging-Based Online Social Network., , , , , , and . MABS, volume 8235 of Lecture Notes in Computer Science, page 17-33. Springer, (2013)A Multiple Classifier System for Classifying Life Events on Social Media., , and . ICDM Workshops, page 1332-1335. IEEE Computer Society, (2015)