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pro vyhledávání: '"Li, Yuanxiang"'
Due to different seasons, illumination, and atmospheric conditions, the photometric of the acquired image varies greatly, which leads to obvious stitching seams at the edges of the mosaic image. Traditional methods can be divided into two categories,
Externí odkaz:
http://arxiv.org/abs/2411.05557
Autor:
Wang, Yilin, Yu, Yifei, Sun, Kong, Lei, Peixuan, Zhang, Yuxuan, Zio, Enrico, Xia, Aiguo, Li, Yuanxiang
In industry, the reliability of rotating machinery is critical for production efficiency and safety. Current methods of Prognostics and Health Management (PHM) often rely on task-specific models, which face significant challenges in handling diverse
Externí odkaz:
http://arxiv.org/abs/2409.17604
Digital Elevation Model (DEM) plays a fundamental role in remote sensing and photogrammetry. Enhancing the quality of DEM is crucial for various applications. Although multiple types of defects may appear simultaneously in the same DEM, they are comm
Externí odkaz:
http://arxiv.org/abs/2407.01908
psPRF:Pansharpening Planar Neural Radiance Field for Generalized 3D Reconstruction Satellite Imagery
Autor:
Zhang, Tongtong, Li, Yuanxiang
Most current NeRF variants for satellites are designed for one specific scene and fall short of generalization to new geometry. Additionally, the RGB images require pan-sharpening as an independent preprocessing step. This paper introduces psPRF, a P
Externí odkaz:
http://arxiv.org/abs/2406.15707
Non-Euclidean data is frequently encountered across different fields, yet there is limited literature that addresses the fundamental challenge of training neural networks with manifold representations as outputs. We introduce the trick named Deep Ext
Externí odkaz:
http://arxiv.org/abs/2404.00544
Autor:
Zhang, Tongtong, Li, Yuanxiang
Novel view synthesis of satellite images holds a wide range of practical applications. While recent advances in the Neural Radiance Field have predominantly targeted pin-hole cameras, and models for satellite cameras often demand sufficient input vie
Externí odkaz:
http://arxiv.org/abs/2310.07179
Autor:
Zhang, Tongtong, Li, Yuanxiang
Existing NeRF models for satellite images suffer from slow speeds, mandatory solar information as input, and limitations in handling large satellite images. In response, we present SatensoRF, which significantly accelerates the entire process while e
Externí odkaz:
http://arxiv.org/abs/2309.11767
Publikováno v:
Zeitschrift für Kristallographie - New Crystal Structures, Vol 239, Iss 2, Pp 251-253 (2024)
C28H27N5O4, monoclinic, P21/c (no. 14), a = 11.3563(15) Å, b = 17.547(2) Å, c = 12.8390(16) Å, β = 101.385(3)°, V = 2508.1(6) Å3, Z = 4, Rgt(F) = 0.0538, wRref(F2) = 0.1329, T = 292(2) K.
Externí odkaz:
https://doaj.org/article/80f9037036f74f4e9b62859398e53b3c
Autor:
Wu, Hongrun, Zhang, MingJie, Xiang, Zhenglong, Chen, Yingpin, Yu, Fei, Xia, Xuewen, Li, Yuanxiang
Publikováno v:
In Neurocomputing 14 January 2025 613
Autor:
Wei, Xian, Huang, Yanhui, Xu, Yangyu, Chen, Mingsong, Lan, Hai, Li, Yuanxiang, Wang, Zhongfeng, Tang, Xuan
With the proliferation of mobile devices and the Internet of Things, deep learning models are increasingly deployed on devices with limited computing resources and memory, and are exposed to the threat of adversarial noise. Learning deep models with
Externí odkaz:
http://arxiv.org/abs/2112.13551