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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-05-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-3-2022/33/2022/isprs-annals-V-3-2022-33-2022.pdf |