Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yihang Zhi"'
Autor:
Yikui Zhai, Hui Ma, He Cao, Wenbo Deng, Jian Liu, Zhongyi Zhang, Huixin Guan, Yihang Zhi, Jinxing Wang, Jihua Zhou
Publikováno v:
The Journal of Engineering (2019)
An effective Max-Fire CNN model MF-SarNet for synthetic aperture radar (SAR) automatic target recognition (ATR) is presented, here. By selecting the convolution kernel of the Fire module in the network, the parameters are reduced to obtain the effect
Externí odkaz:
https://doaj.org/article/9fad705300fe48d896e13ca1497c125e
Autor:
Yikui Zhai, Hui Ma, Jian Liu, Wenbo Deng, Lijuan Shang, Bing Sun, Ziyi Jiang, Huixin Guan, Yihang Zhi, Xi Wu, Jihua Zhou
Publikováno v:
The Journal of Engineering (2019)
Utilising neural networks to learn and extract valuable features has achieved satisfactory performance for synthetic aperture radar automatic target recognition (SAR ATR). However, such target recognition capability could be seriously limited by seve
Externí odkaz:
https://doaj.org/article/e5ce692d10ea4298bf840e5e40f31093
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2978e7c46a11d6ffcde85fcafbbf63ee
https://doi.org/10.1109/igarss46834.2022.9883367
https://doi.org/10.1109/igarss46834.2022.9883367
Autor:
Cao He, Zhongyi Zhang, Zhou Jihua, Guan Huixin, Jian Liu, Wenbo Deng, Jinxing Wang, Yihang Zhi, Yikui Zhai, Hui Ma
Publikováno v:
The Journal of Engineering (2019)
An effective Max-Fire CNN model MF-SarNet for synthetic aperture radar (SAR) automatic target recognition (ATR) is presented, here. By selecting the convolution kernel of the Fire module in the network, the parameters are reduced to obtain the effect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::982506f4e06e1cd2b67348e8cc4f8a75
https://doi.org/10.1049/joe.2019.0218
https://doi.org/10.1049/joe.2019.0218
Publikováno v:
Procedia Computer Science. 131:626-632
To improve the control performance of anti-swinging and the orientation of two-dimensional bridge crane, a novel dynamic sliding mode variable structure control algorithm is presented here. The proposed controller can ensure global stability through
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbece34a99a124878be4e9b24f04eba2
https://doi.org/10.1016/j.procs.2018.04.305
https://doi.org/10.1016/j.procs.2018.04.305
Publikováno v:
Procedia Computer Science. 131:361-366
Fast and accurate tracking is ultimate important to dynamic overhead cranes control. This work presents a simple yet effective fast dynamic overhead cranes tracking method, enabling it to be applied to accurate and real time controlled. Firstly, a sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f21e1dcec16d329da011b361fb5d77f9
https://doi.org/10.1016/j.procs.2018.04.175
https://doi.org/10.1016/j.procs.2018.04.175
Autor:
Yihang Zhi, Yikui Zhai, Guan Huixin, Ke Qirui, Wu Xi, Ying Xu, Ruiming Li, Zhou Jihua, Zheng Yu
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030343866
Aiming at improving the efficiency and the accuracy of the base station antenna inspection, a new method is proposed to use the deep learning algorithm YOLO v3 algorithm combined with geometric mathematics to detect the downtilt angle of the antenna
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0b9070c0840d0e88257701696872aae
https://doi.org/10.1007/978-3-030-34387-3_81
https://doi.org/10.1007/978-3-030-34387-3_81
Autor:
Wu Xi, Guan Huixin, Wenbo Deng, Ziyi Jiang, Hui Ma, Jian Liu, Yihang Zhi, Lijuan Shang, Bing Sun, Zhou Jihua, Yikui Zhai
Publikováno v:
The Journal of Engineering (2019)
Utilising neural networks to learn and extract valuable features has achieved satisfactory performance for synthetic aperture radar automatic target recognition (SAR ATR). However, such target recognition capability could be seriously limited by seve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1330e1fc7e497a28ff4f21f9835e08d
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0219
https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0219
Autor:
Gan Junying, Ying Xu, Yihang Zhi, Fabio Scotti, Chen Lufei, Yikui Zhai, Lu Cao, Junying Zeng, Wengbo Deng, Vincenzo Piuri
Publikováno v:
2018 14th IEEE International Conference on Signal Processing (ICSP).
In this paper, a novel multi-color feature selection method is proposed for person re-identification. Firstly, multi-color features, which consisting of HSV, LAB, RGB and nRnG color features, were extracted and concatenated into a whole feature vecto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78d36807f36ff8e7396e7f53750d95dd
https://doi.org/10.1109/icsp.2018.8652340
https://doi.org/10.1109/icsp.2018.8652340
Autor:
Gan Junying, Cao He, Lu Cao, Vincenzo Piuri, Fabio Scotti, Wenbo Deng, Wang Jinxin, Junying Zeng, Yikui Zhai, Yihang Zhi, Hui Ma
Publikováno v:
Biometric Recognition ISBN: 9783319979083
CCBR
CCBR
Traditional feature extraction methods, such as Gabor filter and competitive coding, have been widely used in finger-knuckle-print (FKP) recognition. However, these methods focus on manually designed features which may not achieve satisfying results
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ade649756ef283e35fa7f5e4003f21d7
https://doi.org/10.1007/978-3-319-97909-0_2
https://doi.org/10.1007/978-3-319-97909-0_2