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of 5
pro vyhledávání: '"Jiang, Baisong"'
Autor:
Bai, Haowen, Zhao, Zixiang, Zhang, Jiangshe, Wu, Yichen, Deng, Lilun, Cui, Yukun, Xu, Shuang, Jiang, Baisong
Image fusion aims to combine information from multiple source images into a single one with more comprehensive informational content. The significant challenges for deep learning-based image fusion algorithms are the lack of a definitive ground truth
Externí odkaz:
http://arxiv.org/abs/2312.07943
Autor:
Wei, Xiaoli, Zhang, Chunxia, Wang, Hongtao, Tan, Chengli, Xiong, Deng, Jiang, Baisong, Zhang, Jiangshe, Kim, Sang-Woon
Accurate interpolation of seismic data is crucial for improving the quality of imaging and interpretation. In recent years, deep learning models such as U-Net and generative adversarial networks have been widely applied to seismic data interpolation.
Externí odkaz:
http://arxiv.org/abs/2307.04226
Autor:
Wei, Xiaoli, Zhang, Chunxia, Wang, Hongtao, Tan, Chengli, Xiong, Deng, Jiang, Baisong, Zhang, Jiangshe, Kim, Sang-Woon
The incompleteness of the seismic data caused by missing traces along the spatial extension is a common issue in seismic acquisition due to the existence of obstacles and economic constraints, which severely impairs the imaging quality of subsurface
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fea2b0ddf2ee0269c29a15bfeb648618
http://arxiv.org/abs/2307.04226
http://arxiv.org/abs/2307.04226
Autor:
Wei, Xiaoli, Zhang, Chunxia, Wang, Hongtao, Tan, Chengli, Xiong, Deng, Jiang, Baisong, Zhang, Jiangshe, Kim, Sang-Woon
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing; 2024, Vol. 62 Issue: 1 p1-17, 17p
Akademický článek
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