Coastal Land Cover Classification of High-Resolution Remote Sensing Images Using Attention-Driven Context Encoding Network

Low inter-class variance and complex spatial details exist in ground objects of the coastal zone, which leads to a challenging task for coastal land cover classification (CLCC) from high-resolution remote sensing images. Recently, fully convolutional neural networks have been widely used in CLCC. Ho...

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Detalles Bibliográficos
Autores principales: Chen, Jifa, Chen, Gang, Wang, Lizhe, Fang, Bo, Zhou, Ping, Zhu, Mingjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763023/
https://www.ncbi.nlm.nih.gov/pubmed/33302547
http://dx.doi.org/10.3390/s20247032

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763023/
https://www.ncbi.nlm.nih.gov/pubmed/33302547
http://dx.doi.org/10.3390/s20247032

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