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Improving optimum-path forest learning using bag-of-classifiers and confidence measures.

, and . Pattern Anal. Appl., 22 (2): 703-716 (2019)

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Stroke Lesion Detection Using Convolutional Neural Networks., , , , and . IJCNN, page 1-6. IEEE, (2018)Black Hole Algorithm for non-technical losses characterization., , , and . LASCAS, page 1-4. IEEE, (2015)A new approach to contextual learning using interval arithmetic and its applications for land-use classification., and . Pattern Recognit. Lett., (2016)Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques., , , , and . J. Comput. Sci., (2015)Land-cover classification through sequential learning-based optimum-path forest., , , and . IGARSS, page 76-79. IEEE, (2015)Fine-tuning Deep Belief Networks using Harmony Search., , and . Appl. Soft Comput., (2016)κ-Entropy Based Restricted Boltzmann Machines., , , and . IJCNN, page 1-8. IEEE, (2019)An incremental Optimum-Path Forest classifier and its application to non-technical losses identification., , , , and . Comput. Electr. Eng., (2021)IFTrace: Video segmentation of deformable objects using the Image Foresting Transform., , , , , and . Comput. Vis. Image Underst., 116 (2): 274-291 (2012)Nature-inspired optimum-path forest., , and . Evol. Intell., 16 (1): 317-328 (February 2023)