Semantic Segmentation of Building Roof in Dense Urban Environment with Deep Convolutional Neural Network: A Case Study Using GF2 VHR Imagery in China

This paper presents a novel approach for semantic segmentation of building roofs in dense urban environments with a Deep Convolution Neural Network (DCNN) using Chinese Very High Resolution (VHR) satellite (i.e., GF2) imagery. To provide an operational end-to-end approach for accurately mapping buil...

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Detalles Bibliográficos
Autores principales: Qin, Yuchu, Wu, Yunchao, Li, Bin, Gao, Shuai, Liu, Miao, Zhan, Yulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427113/
https://www.ncbi.nlm.nih.gov/pubmed/30866539
http://dx.doi.org/10.3390/s19051164

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427113/
https://www.ncbi.nlm.nih.gov/pubmed/30866539
http://dx.doi.org/10.3390/s19051164

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