Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Baidong Yao"'
Autor:
Huiyao Wan, Jie Chen, Zhixiang Huang, Yun Feng, Zheng Zhou, Xiaoping Liu, Baidong Yao, Tao Xu
Publikováno v:
IEEE Access, Vol 9, Pp 94586-94600 (2021)
High-resolution remote sensing image scene classification has attracted widespread attention as a basic earth observation task. Remote sensing scene classification aims to assign specific semantic labels to remote sensing scene images to serve specif
Externí odkaz:
https://doaj.org/article/71e200475b324d57a02073615ba3547a
Publikováno v:
Remote Sensing, Vol 14, Iss 22, p 5659 (2022)
The spaceborne P-band fully polarimetric synthetic aperture radar (SAR) working system is highly susceptible to the scintillation effects induced by ionospheric irregularities due to its low carrier frequency. The scintillation phase error (SPE) is a
Externí odkaz:
https://doaj.org/article/2485c742e3cc4d1086760c5a752b31ce
Publikováno v:
IEEE Access, Vol 7, Pp 3181-3193 (2019)
A low-frequency spaceborne synthetic aperture radar (SAR) working system, e.g., operating at the $L$ -band or $P$ -band, has great advantages of military target detection and biomass monitoring. Nevertheless, it is more susceptible to ionospheric eff
Externí odkaz:
https://doaj.org/article/bb06cc6ca4f042a9b62dbf5f670ba45c
Autor:
Runfan Xia, Jie Chen, Zhixiang Huang, Huiyao Wan, Bocai Wu, Long Sun, Baidong Yao, Haibing Xiang, Mengdao Xing
Publikováno v:
Remote Sensing, Vol 14, Iss 6, p 1488 (2022)
Synthetic-aperture radar (SAR) image target detection is widely used in military, civilian and other fields. However, existing detection methods have low accuracy due to the limitations presented by the strong scattering of SAR image targets, unclear
Externí odkaz:
https://doaj.org/article/e4d15d44fb344bdeb3d8a7e790fd3622
Publikováno v:
The Journal of Engineering (2019)
Spaceborne synthetic aperture radar (SAR) systems operating at low frequency, such as L- and P-bands, are significantly influenced by ionospheric effects. One of the remarkable effects is Faraday rotation (FR), which is known as a serious error sourc
Externí odkaz:
https://doaj.org/article/8f38c822f6ce44199dffe9398b3e4a51
Autor:
Wenguang Xiao, Baidong Yao
Publikováno v:
The Journal of Engineering (2019)
There are a large number of high-energy particles in the space. These high-energy particles induce a single-event upset effect on DSP, FPGA, and other programmable digital controllers inside the beam-steering unit, which can produce unpredictable and
Externí odkaz:
https://doaj.org/article/b9abc5ed46ab44bf807a2a2a4f0f2b87
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems. 58:1266-1282
This paper proposes an Automatic Identification System (AIS) data aided Rayleigh constant false alarm rate (AIS-RCFAR) ship detection algorithm of multiple-target environment in synthetic aperture radar (SAR) images. This method aims to improve the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5ef656a4f4321a61f478feb251e2701
https://doi.org/10.1109/taes.2021.3111849
https://doi.org/10.1109/taes.2021.3111849
Autor:
Zheng Zhou, Jie Chen, Zhixiang Huang, Huiyao Wan, Pei Chang, Zhao Li, Baidong Yao, BoCai Wu, Long Sun, Mengdao Xing
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d50c57728bf3175d568394cd48c6da3d
https://doi.org/10.1109/tgrs.2022.3192996
https://doi.org/10.1109/tgrs.2022.3192996
Autor:
Huiyao Wan, Jie Chen, Zhixiang Huang, RunFan Xia, BoCai Wu, Long Sun, Baidong Yao, Xiaoping Liu, Mengdao Xing
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d68768c2cc9e4dbbecf49a0d6f06dbe3
https://doi.org/10.1109/tgrs.2021.3137817
https://doi.org/10.1109/tgrs.2021.3137817
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-14
In order to more efficiently mine the features of polarimetric synthetic aperture radar (PolSAR) and establish a more appropriate classification model, this article proposes an improved convolutional autoencoder (ICAE) based on texture feature fusion
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe2fb5b6461ae378f1cf07d49d78a10d
https://doi.org/10.1109/tgrs.2021.3131986
https://doi.org/10.1109/tgrs.2021.3131986