A deep inverse convolutional neural network-based semantic classification method for land cover remote sensing images

Abstract The imbalance of land cover categories is a common problem. Some categories appear less frequently in the image, while others may occupy the vast majority of the proportion. This imbalance can lead the classifier to tend to predict categories with higher frequency of occurrence, while the r...

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Autori principali:	Ming Wang, Anqi She, Hao Chang, Feifei Cheng, Heming Yang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2024-03-01
Serie:	Scientific Reports
Soggetti:	Deep inverse convolutional neural network Land cover Remote sensing images Semantic classification Semantic segmentation Feature extraction
Accesso online:	https://doi.org/10.1038/s41598-024-57408-0
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