Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Binqiang Si"'
Autor:
Yajing Zhang, Binqiang Si
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract With fossil energy reducing year by year, more and more attention to the new energy sources greatly promotes the development of the distributed power generation system, especially the low-power photovoltaic system. However, the power injecte
Externí odkaz:
https://doaj.org/article/73c6442d49f846c286dcdcc512b0021d
Autor:
Huiying Wang, Chunping Wang, Qiang Fu, Binqiang Si, Dongdong Zhang, Renke Kou, Ying Yu, Changfeng Feng
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15269-15287 (2024)
With the rapid advancements in deep learning technology, various deep learning-based object detection algorithms have found extensive applications in UAV-related tasks. However, motivated by the fact that current object detection algorithms for unimo
Externí odkaz:
https://doaj.org/article/2cf0880d0fb44bc5bb3c474eb76085e9
Publikováno v:
Applied Sciences, Vol 14, Iss 5, p 1868 (2024)
To ensure precise and real-time perception of high-speed roadway conditions and minimize the potential threats to traffic safety posed by road debris and defects, this study designed a real-time monitoring and early warning system for high-speed road
Externí odkaz:
https://doaj.org/article/cc5f8533c61c42db8b3d99f6eb2054f1
Publikováno v:
Electronics Letters, Vol 58, Iss 16, Pp 623-626 (2022)
Abstract In this paper, the is focus on the online graph learning problems in time‐varying environment. Traditional graph learning methods always assume that the underlying graph is static and that enough training data are available. However, in ma
Externí odkaz:
https://doaj.org/article/1e06097cd3e5456bb23bb08fd3334963
Publikováno v:
Electronics Letters, Vol 57, Iss 13, Pp 520-522 (2021)
Abstract In this letter, a pyramid wavelet convolutional neural network for audio super resolution is presented. Since the audio signal is non‐stationary, previous convolutional neural network based approaches may fail in capturing the details, the
Externí odkaz:
https://doaj.org/article/455e6f526ab34df8ae01783531e23c7e
Publikováno v:
Sensors, Vol 21, Iss 4, p 1415 (2021)
In this paper, we focus on the bandlimited graph signal sampling problem. To sample graph signals, we need to find small-sized subset of nodes with the minimal optimal reconstruction error. We formulate this problem as a subset selection problem, and
Externí odkaz:
https://doaj.org/article/01e2a1039b634e4db4316ae41e9f0ec9
Publikováno v:
IEEE Transactions on Vehicular Technology. 71:9794-9804
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::914037ac7b218d775be76e197bc544d4
https://doi.org/10.1109/tvt.2022.3182874
https://doi.org/10.1109/tvt.2022.3182874
Publikováno v:
IET Radar, Sonar & Navigation. 16:1681-1695
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1fee104bf40509594bf838d5212a02f
https://doi.org/10.1049/rsn2.12289
https://doi.org/10.1049/rsn2.12289
Publikováno v:
In IFAC Proceedings Volumes 2013 46(5):643-649
Publikováno v:
Electronics Letters, Vol 57, Iss 13, Pp 520-522 (2021)
In this letter, a pyramid wavelet convolutional neural network for audio super resolution is presented. Since the audio signal is non‐stationary, previous convolutional neural network based approaches may fail in capturing the details, these method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1da1a9e51c7b85c2a4ba2efcac44c338
https://doi.org/10.1049/ell2.12180
https://doi.org/10.1049/ell2.12180