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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| 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 |