Zobrazeno 1 - 10
of 1 908
pro vyhledávání: '"building extraction"'
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 10, Pp 2712-2726 (2024)
Due to the high similarity between background and buildings in high spatial resolution remote sensing images, which makes it difficult for the network to take into account buildings of different sizes, the pixels in the building boundary region are c
Externí odkaz:
https://doaj.org/article/3fa803bd1b694bedb03ad5bf1b45b565
Publikováno v:
Zhihui kongzhi yu fangzhen, Vol 46, Iss 6, Pp 55-61 (2024)
Aerial imagery can provide rich geographic information. As an important ground object information, quickly and accurately extracting buildings from aerial images can achieve target monitoring, location positioning, and further enrich specific geograp
Externí odkaz:
https://doaj.org/article/a30ad6ca7fbd4cb4aaacd86ddeaf31c9
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Building extraction aims to extract building pixels from remote sensing imagery, which plays a significant role in urban planning, dynamic urban monitoring, and many other applications. UNet3+ is widely applied in building extraction from re
Externí odkaz:
https://doaj.org/article/d67f9fc083234848b494e515851b5a53
Publikováno v:
Geo-spatial Information Science, Pp 1-15 (2024)
The deep learning-based building extraction methods produce different feature maps at different stages of the network, which contain different information features. The detailed information of the feature maps decreases along the depth of the network
Externí odkaz:
https://doaj.org/article/b4d4272b14b44f06b485e7de067be1e5
Autor:
Wenxiang Jiang, Yan Chen, Xiaofeng Wang, Menglei Kang, Mengyuan Wang, Xuejun Zhang, Lixiang Xu, Cheng Zhang
Publikováno v:
Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 1, Pp 10-17 (2024)
Extraction of color and texture features of buildings from high-resolution remote sensing images often encounters the problems of interference of background information and varying target scales. In addition, most of the current attention mechanisms
Externí odkaz:
https://doaj.org/article/095741175b80457aa2611a8d1410806d
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTQuick and accurate extraction of un-collapsed buildings from post-disaster High-resolution Remote Sensing Images (HRSIs) is imperative for emergency response. Pre-disaster HRSIs could serve as auxiliary data for training models to expedite th
Externí odkaz:
https://doaj.org/article/721d6f5a553e4453b0741d6801d7e186
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 130, Iss , Pp 103942- (2024)
Buildings play a crucial role in geographic information systems, and advancements in the resolution of remote sensing imagery have facilitated their extraction on a larger scale. However, this progress has simultaneously heightened the requirements f
Externí odkaz:
https://doaj.org/article/f34513a82d49403aa106e2ee1c9f46e3
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 18427-18443 (2024)
Building extraction from remote sensing (RS) image holds a crucial position in the fields of urban planning and sustainable development. In high-resolution (HR) RS images, the characteristics of buildings, including their shapes, structures, and text
Externí odkaz:
https://doaj.org/article/d2e6253e8a3c4f96850352e21157f4ed
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16577-16591 (2024)
Building extraction is a challenging task in remote sensing images (RSI) interpretation. Fusing RSI from different sources, such as high-resolution RSI and LiDAR, is a common strategy to improve the building extraction accuracy. However, the acquisit
Externí odkaz:
https://doaj.org/article/c442f302645643bebf75c85a63b6bba0
Autor:
Shaohan Cao, Dejun Feng, Suning Liu, Wanqi Xu, Hongyu Chen, Yakun Xie, Heng Zhang, Saied Pirasteh, Jun Zhu
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16342-16358 (2024)
Deep learning methods are widely used in building information extraction from remote sensing images (RSIs). However, this task still faces great challenges. First, it is difficult to perform accurate boundary localization due to the complex contextua
Externí odkaz:
https://doaj.org/article/b03179e73c5c4f0baff7c3022abe05a6