Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Pucheng Zhou"'
Autor:
Congju Zuo, Yong Cheng, Hongtao Pan, Guodong Qin, Pucheng Zhou, Liang Xia, Huan Wang, Ruijuan Zhao, Yongqiang Lv, Xiaoyan Qin, Weihua Wang, Qingxi Yang
Publikováno v:
Nuclear Engineering and Technology, Vol 56, Iss 10, Pp 4412-4422 (2024)
The CFETR multipurpose overload robot (CMOR) is a critical component of the fusion reactor remote handling system. To accurately calculate and visualize the structural deformation and stress characteristics of the CMOR motion process, this paper firs
Externí odkaz:
https://doaj.org/article/66c40bc19af749d2b5cf47c83cc99cd1
Autor:
Congju Zuo, Guodong Qin, Hongtao Pan, Liang Xia, Feng Wang, Pucheng Zhou, Xiaoyan Qin, Ning Shi, Leiji Lu, Ruijuan Zhao, Chenhui Wan, Guangnan Luo, Weihua Wang, Yong Cheng
Publikováno v:
Applied Sciences, Vol 13, Iss 18, p 10487 (2023)
The CFETR multi-purpose overload robot (CMOR) is a key subsystem of the remote handling system of the China fusion engineering test reactor (CFETR). This paper first establishes the kinematic and dynamic models of CMOR and analyzes the working proces
Externí odkaz:
https://doaj.org/article/a9a0188599a047dc9c376a410e992f36
Publikováno v:
9th Symposium on Novel Photoelectronic Detection Technology and Applications (NDTA2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46872fc87c4c6fc6fd0968d106712657
https://doi.org/10.1117/12.2662886
https://doi.org/10.1117/12.2662886
Publikováno v:
2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76be4d72698f0a04c31deb843f445a70
https://doi.org/10.1109/cisp-bmei53629.2021.9624222
https://doi.org/10.1109/cisp-bmei53629.2021.9624222
Publikováno v:
IET Image Processing. 13:1835-1845
Structure–texture decomposition is one of the fundamental branches of computer vision and image processing. It is not only beneficial to image understanding but also to subsequent object recognition and tracking. However, diversity and complexity o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdf9a591150293ffefc6d456f174733e
https://doi.org/10.1049/iet-ipr.2018.5133
https://doi.org/10.1049/iet-ipr.2018.5133
Publikováno v:
Twelfth International Conference on Graphics and Image Processing (ICGIP 2020).
When capturing images in low-light conditions, the images are often degraded with low visibility and severe noise. To improve the visual quality and repress the noise simultaneously, a kind of low-light image enhancement method via layer decompositio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb432c525ef64bb5af639ae00a4843f4
https://doi.org/10.1117/12.2589353
https://doi.org/10.1117/12.2589353
Autor:
Xiaomin Ma, Hui Zhang, Junjian Liu, Ling Yao, Zongming Tao, Yingjian Wang, Pucheng Zhou, Chenbo Xie, Shenhao Wang, Huihui Shan, Dong Liu
Publikováno v:
Optics Communications. 410:730-732
Aerosol extinction coefficient profile is an essential parameter for atmospheric radiation model. It is difficult to get higher signal to noise ratio (SNR) of backscattering lidar from the ground to the tropopause especially in near range. Higher SNR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07a2825b4f987a246674109996ac7b57
https://doi.org/10.1016/j.optcom.2017.11.015
https://doi.org/10.1016/j.optcom.2017.11.015
Publikováno v:
Fifth Conference on Frontiers in Optical Imaging Technology and Applications.
Low-light image enhancement is a challenging problem in the field of computer vision. In order to obtain more pleasing enhancement results, a low-light image enhancement method via joint convolutional sparse representation is proposed. The method is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8587dd2dd8c5d24e0611f726df45ff2c
https://doi.org/10.1117/12.2511946
https://doi.org/10.1117/12.2511946
Publikováno v:
2018 International Conference on Image and Video Processing, and Artificial Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20e16eedaaf6e8fda24aedff13de9f98
https://doi.org/10.1117/12.2514014
https://doi.org/10.1117/12.2514014
Publikováno v:
CISP-BMEI
Most existing graph cut methods does not perform well for the low-contrast and high-noisy natural images. In this paper, we present an improved image segmentation method based on TurboPixel and kernel graph cuts to solve this problem. The TurboPixel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d2d7fdc3cdeec1abf69ce332f88056ea
https://doi.org/10.1109/cisp-bmei.2017.8301984
https://doi.org/10.1109/cisp-bmei.2017.8301984