Zobrazeno 1 - 10
of 220
pro vyhledávání: '"Wenkai LU"'
Autor:
Leilei SHUI, Kunqi QIU, Huan WAN, Shengli GONG, Wenkai LU, Wenyan WEI, Yonghao WANG, Yongzhao YU
Publikováno v:
Shiyou shiyan dizhi, Vol 46, Iss 6, Pp 1362-1370 (2024)
The identification of paleontological fossil types and their distribution provides important information for geochronological, paleoenvironmental studies, and oil and gas exploration. However, traditional fossil identification methods are time-consum
Externí odkaz:
https://doaj.org/article/9ed0859d75e0416da57e4229e868e0de
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. 61:1-13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5aa784bfe4ce5798033fe31fdecda546
https://doi.org/10.1109/tgrs.2023.3234568
https://doi.org/10.1109/tgrs.2023.3234568
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fbe8b1854004f99107370b135fced26
https://doi.org/10.1109/tgrs.2023.3247880
https://doi.org/10.1109/tgrs.2023.3247880
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 Journal of Biomedical and Health Informatics. :1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42c6484bc384d467825599f19d98228b
https://doi.org/10.1109/jbhi.2023.3236989
https://doi.org/10.1109/jbhi.2023.3236989
Publikováno v:
Information Sciences. 617:416-434
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3638af9e180623accb83f1b31d340c6
https://doi.org/10.1016/j.ins.2022.10.093
https://doi.org/10.1016/j.ins.2022.10.093
Publikováno v:
Journal of Geophysics and Engineering. 19:550-561
Seismic impedance inversion is one of the key techniques for quantitative seismic interpretation. Most conventional post-stack seismic impedance inversion approaches are based on the linear theory, whereas the relationship between seismic response an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32cd73a018ecdc3d8c81339b334ae485
https://doi.org/10.1093/jge/gxac035
https://doi.org/10.1093/jge/gxac035
Publikováno v:
Petroleum Science. 19:147-161
Deep learning has achieved great success in a variety of research fields and industrial applications. However, when applied to seismic inversion, the shortage of labeled data severely influences the performance of deep learning-based methods. In orde
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdd848ddef7b24c7e449fafd41b40a04
https://doi.org/10.1016/j.petsci.2021.09.038
https://doi.org/10.1016/j.petsci.2021.09.038
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ea0fd05cb60bc47d597f2392aa966fc
https://doi.org/10.1109/tgrs.2022.3205301
https://doi.org/10.1109/tgrs.2022.3205301