Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Xiren Zhou"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 8299-8308 (2022)
Ground penetrating radar (GPR) has been widely used as a nondestructive tool to image the subsurface. When the GPR's detecting direction is perpendicular to the orientation of a buried pipeline, a hyperbolic feature would be formed on the GPR B-scan
Externí odkaz:
https://doaj.org/article/68877f0b89bd4a669c067b0d7daaa618
Publikováno v:
IEEE Access, Vol 8, Pp 118114-118124 (2020)
Underground pipeline mapping is important in urban construction. There are few specific procedures and approaches to map underground pipelines using ground penetration radar (GPR) without knowing the number of buried pipelines. In this paper, an auto
Externí odkaz:
https://doaj.org/article/a579c5242706470793f22d241168234e
Autor:
Xiangyu Wang, Lyuzhou Chen, Taiyu Ban, Derui Lyu, Yifeng Guan, Xingyu Wu, Xiren Zhou, Huanhuan Chen
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-13
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::622768aa27dbfc8ec8f1b5ee5db3c9d1
https://doi.org/10.1109/tgrs.2023.3241402
https://doi.org/10.1109/tgrs.2023.3241402
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-12
With the rapid expansion of urban areas and the increasingly use of electricity, the need for locating buried cables is becoming urgent. In this paper, a noval method to locate underground cables based on Ground Penetrating Radar (GPR) and Gaussian-p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09495b1c9f3e115c1d0eedc93e9266f0
https://doi.org/10.1109/tgrs.2022.3181380
https://doi.org/10.1109/tgrs.2022.3181380
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f12dc85df6f847619ec338721e4816d8
https://doi.org/10.1109/tkde.2022.3198689
https://doi.org/10.1109/tkde.2022.3198689
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c63ba3b07706136f75a403037ee336b
https://doi.org/10.1109/tgrs.2022.3200153
https://doi.org/10.1109/tgrs.2022.3200153
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 59:10047-10061
Detecting changed regions in paired satellite images plays a key role in many remote sensing applications. The evolution of recent techniques could provide satellite images with a very high spatial resolution (VHR) but made it challenging to apply im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86aafb1aae8517cdf05bd6e74747575a
https://doi.org/10.1109/tgrs.2020.3043766
https://doi.org/10.1109/tgrs.2020.3043766
Publikováno v:
2022 IEEE Symposium Series on Computational Intelligence (SSCI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62a2362286322abb80cebe3caecad0cd
https://doi.org/10.1109/ssci51031.2022.10022276
https://doi.org/10.1109/ssci51031.2022.10022276
Publikováno v:
2022 8th International Conference on Big Data and Information Analytics (BigDIA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::717b62cde07b467d1faaa0a8e0f57785
https://doi.org/10.1109/bigdia56350.2022.9874057
https://doi.org/10.1109/bigdia56350.2022.9874057
Publikováno v:
IEEE transactions on neural networks and learning systems.
As data sources become ever more numerous with increased feature dimensionality, feature selection for multiview data has become an important technique in machine learning. Semi-supervised multiview feature selection (SMFS) focuses on the problem of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09729c2f953b8b995f44b867f743de9f
https://pubmed.ncbi.nlm.nih.gov/35939477
https://pubmed.ncbi.nlm.nih.gov/35939477