Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Jing, Weipeng"'
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 6006105
Hyperspectral images have significant applications in various domains, since they register numerous semantic and spatial information in the spectral band with spatial variability of spectral signatures. Two critical challenges in identifying pixels o
Externí odkaz:
http://arxiv.org/abs/2307.10186
The building planar graph reconstruction, a.k.a. footprint reconstruction, which lies in the domain of computer vision and geoinformatics, has been long afflicted with the challenge of redundant parameters in conventional convolutional models. Theref
Externí odkaz:
http://arxiv.org/abs/2306.15035
Autor:
Li, Xun, Yao, Minghe, Li, Lingling, Ma, Huifen, Sun, Yiran, Lu, Xiangpeng, Jing, Weipeng, Nie, Shanshan
Publikováno v:
In Phytomedicine July 2024 129
In the area of geographic information processing. There are few researches on geographic text classification. However, the application of this task in Chinese is relatively rare. In our work, we intend to implement a method to extract text containing
Externí odkaz:
http://arxiv.org/abs/2101.11424
Publikováno v:
In Information Sciences October 2023 645
High-resolution aerial images have a wide range of applications, such as military exploration, and urban planning. Semantic segmentation is a fundamental method extensively used in the analysis of high-resolution aerial images. However, the ground ob
Externí odkaz:
http://arxiv.org/abs/1907.03089
Building footprint extraction from high-resolution aerial images is always an essential part of urban dynamic monitoring, planning and management. It has also been a challenging task in remote sensing research. In recent years, deep neural networks h
Externí odkaz:
http://arxiv.org/abs/1903.12337
Autor:
Chen, Guangsheng, Lu, Hailiang, Zou, Weitao, Li, Linhui, Emam, Mahmoud, Chen, Xuebin, Jing, Weipeng, Wang, Jian, Li, Chao
Publikováno v:
In Journal of King Saud University - Computer and Information Sciences March 2023 35(3):259-273
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