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WEAKLY SUPERVISED LEARNING FOR TREELINE ECOTONE CLASSIFICATION BASED ON AERIAL ORTHOIMAGES AND AN ANCILLARY DSM

Convolutional neural networks (CNNs) effectively classify standard datasets in remote sensing (RS). Yet, real-world data are more difficult to classify using CNNs because these networks require relatively large amounts of training data. To reduce training data requirements, two approaches can be fol...

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Main Authors: J. Dvořák, M. Potůčková, V. Treml
Formato: Artigo
Idioma:Inglês
Publicado em: Copernicus Publications 2022-05-01
Colecção:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Acesso em linha:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-3-2022/33/2022/isprs-annals-V-3-2022-33-2022.pdf
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