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Evaluation of Classifiers for Image Segmentation: Applications for Eucalypt Forest Inventory
[article]
2017
arXiv
pre-print
The task of counting eucalyptus trees from aerial images collected by unmanned aerial vehicles (UAVs) has been frequently explored by techniques of estimation of the basal area, i.e, by determining the expected number of trees based on sampling techniques. An alternative is the use of machine learning to identify patterns that represent a tree unit, and then search for the occurrence of these patterns throughout the image. This strategy depends on a supervised image segmentation step to define
arXiv:1703.09436v1
fatcat:5j76z7vjunca3d3muhgixutchy