A method for extracting buildings from remote sensing images based on 3DJA-UNet3+-Reference-Cited by-同舟云学术

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A method for extracting buildings from remote sensing images based on 3DJA-UNet3+

Published:2024-08-17 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Li Yingjian,Li Yonggang,Zhu Xiangbin,Fang Haojie,Ye Lihua

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Jiaxing Science and Technology Project

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-70019-z.pdf

Reference59 articles.

1. Roy, S., Majumder, S., Bose, A. & Chowdhury, I. R. Spatial heterogeneity in the urban household living conditions: A-gis-based spatial analysis. Ann. GIS 1–24 (2024).

2. Gui, S., Song, S., Qin, R. & Tang, Y. Remote sensing object detection in the deep learning era-a review. Remote Sens. 16, 327 (2024).

3. Wei, S., Zhang, T., Ji, S., Luo, M. & Gong, J. Buildmapper: A fully learnable framework for vectorized building contour extraction. ISPRS J. Photogramm. Remote. Sens. 197, 87–104 (2023).

4. Zhang, L. & Zhang, L. Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities. IEEE Geosci. Remote Sens. Mag. 10, 270–294 (2022).

5. Razzak, M. T. et al. Multi-spectral multi-image super-resolution of sentinel-2 with radiometric consistency losses and its effect on building delineation. ISPRS J. Photogramm. Remote. Sens. 195, 1–13 (2023).

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