Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yinshuo Li"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7674-7683 (2024)
With the continuous development of computer technology and significant improvements in computing power, deep learning has found increasing applications in seismic stratigraphy interpretation, showcasing notable advancements over traditional methods.
Externí odkaz:
https://doaj.org/article/e509a26b0fdf4701baff003ae040a59f
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-10
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb46852f37ca4f8573b9ec4b0ad881f9
https://doi.org/10.1109/tgrs.2023.3253888
https://doi.org/10.1109/tgrs.2023.3253888
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-12
Recently, a multitask learning framework named M: multitask, R: global residual skip connection structure, U: encoder-decoder structure of U-Net, D: dense skip connection structure, and SR: super-resolution (M-RUDSR) has successfully improved the acc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca2ad34f81a84a48cc438171b0e0a82e
https://doi.org/10.1109/tgrs.2021.3075622
https://doi.org/10.1109/tgrs.2021.3075622
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f72cf6460d01976d9c5a5b5b23e4c8a
https://doi.org/10.1109/tgrs.2022.3225449
https://doi.org/10.1109/tgrs.2022.3225449
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f98d72237c628a8f879b8708822a0a17
https://doi.org/10.1109/tgrs.2022.3193297
https://doi.org/10.1109/tgrs.2022.3193297
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:8022-8033
Full waveform inversion (FWI) is a powerful tool for estimating the underground velocity model. However, it is computationally expensive and the resulting models tend to be not accurate enough. Thus, to improve the efficiency and accuracy of FWI, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0cb8d7bdaeaa4f632da07bbc70fcca1c
https://doi.org/10.1109/tgrs.2020.3034502
https://doi.org/10.1109/tgrs.2020.3034502