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ReVeS Participation - Tree Species Classification Using Random Forests and Botanical Features.

, , , , , , and . CLEF (Online Working Notes/Labs/Workshop), volume 1178 of CEUR Workshop Proceedings, CEUR-WS.org, (2012)

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A fusion system for tree species recognition through leaves and barks., , and . SSCI, page 1-8. IEEE, (2016)Bark and leaf fusion systems to improve automatic tree species recognition., , , , , and . Ecol. Informatics, (2018)An interactive fuzzy fusion system applied to change detection in SAR images., , , , and . FUZZ-IEEE, page 932-937. IEEE, (2002)ReVeS Participation - Tree Species Classification Using Random Forests and Botanical Features., , , , , , and . CLEF (Online Working Notes/Labs/Workshop), volume 1178 of CEUR Workshop Proceedings, CEUR-WS.org, (2012)A Genetic-Algorithm-Based Fusion System Optimization for 3D Image Interpretation., , and . CIARP, volume 6419 of Lecture Notes in Computer Science, page 338-345. Springer, (2010)Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy., , , and . ICPR, page 1496-1501. IEEE Computer Society, (2014)Sub-classification strategies for tree species recognition., , and . ICPR, page 2139-2144. IEEE, (2016)Application of Quantitative MCDA Methods for Parameter Setting Support of an Image Processing System., and . MDAI, volume 7647 of Lecture Notes in Computer Science, page 341-354. Springer, (2012)A 3D image-segmented evaluation procedure in a cooperative fusion system context., , , and . FUSION, page 1-8. IEEE, (2007)Fusion system based on belief functions theory and approximated belief functions for tree species recognition., , and . IPTA, page 1-6. IEEE, (2016)