Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Yuke Guo"'
Publikováno v:
IET Computer Vision, Vol 15, Iss 6, Pp 393-404 (2021)
Abstract This paper addresses the 3D face reconstruction and semantic annotation from a single‐view noisy depth image. A deep neural network‐based coarse‐to‐fine framework is presented to take advantage of 3D morphable model (3DMM) regression
Externí odkaz:
https://doaj.org/article/d0030d737e044644b5cf6faa4293ca4f
Autor:
Zhongwei Ji, Yuke Guo, Yuqi He, Luyu Zhao, Guan-Long Huang, Chuangzhu Zhou, Qinjuan Zhang, Wei Lin
Publikováno v:
IEEE Access, Vol 9, Pp 151023-151036 (2021)
In this paper, an effective method for developing a multi-feed multiple-input multiple-output (MIMO) antenna system using the metal rims of a mobile phone without any structural interruption on the long edge frames is proposed. Instead of traditional
Externí odkaz:
https://doaj.org/article/b374aca28387479f878608f2e59731ce
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 217, Iss , Pp 112230- (2021)
Cadmium (Cd) has been widely used in industry and can accumulate in the water, soil, and food. Meretrix meretrix is one of the marine shellfishes cultivated for economic purpose in China. The increasing Cd levels in coastal marine water could adverse
Externí odkaz:
https://doaj.org/article/cb16ea36b40240569195cc905edacd6c
Autor:
Yikun Jiang, Yuru Pei, Peixin Li, Yungeng Zhang, Yuke Guo, Yi Fan, Gui Chen, Fanfan Dai, Tianmin Xu, Xiaoru Yuan, Hongbin Zha
Publikováno v:
IEEE Transactions on Computational Imaging. 8:972-985
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::041047d14a9432e3c8ee82159825888c
https://doi.org/10.1109/tci.2022.3216202
https://doi.org/10.1109/tci.2022.3216202
Publikováno v:
2022 International Applied Computational Electromagnetics Society Symposium (ACES-China).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb41ad16d494e87f61960bbd13263a2a
https://doi.org/10.1109/aces-china56081.2022.10065016
https://doi.org/10.1109/aces-china56081.2022.10065016
Publikováno v:
2022 International Applied Computational Electromagnetics Society Symposium (ACES-China).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3dd264fe822500d7a6831db78a9f9f61
https://doi.org/10.1109/aces-china56081.2022.10065318
https://doi.org/10.1109/aces-china56081.2022.10065318
Publikováno v:
IET Computer Vision, Vol 15, Iss 6, Pp 393-404 (2021)
This paper addresses the 3D face reconstruction and semantic annotation from a single‐view noisy depth image. A deep neural network‐based coarse‐to‐fine framework is presented to take advantage of 3D morphable model (3DMM) regression and per
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc8a196f1e5234f8200e6c501de3e3b1
https://doi.org/10.1049/cvi2.12024
https://doi.org/10.1049/cvi2.12024
Autor:
Wei Bai, Meng Liu, Yuru Pei, Wenhai Wu, Gengyu Ma, Yicheng Zhong, Yuke Guo, Peixin Li, Hongbin Zha
Publikováno v:
IEEE Transactions on Biometrics, Behavior, and Identity Science. 3:6-15
Depth images are widely used in 3D head pose estimation and face reconstruction. The device-specific noise and the lack of textual constraints pose a major problem for estimating a nonrigid deformable face from a single noisy depth image. In this art
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aeb6397a61e9eba9a399d79241b10a71
https://doi.org/10.1109/tbiom.2020.3025466
https://doi.org/10.1109/tbiom.2020.3025466
Autor:
Chuangzhu Zhou, Wei Lin, Zhongwei Ji, Qinjuan Zhang, Yuke Guo, Guan-Long Huang, Luyu Zhao, Yuqi He
Publikováno v:
IEEE Access, Vol 9, Pp 151023-151036 (2021)
In this paper, an effective method for developing a multi-feed multiple-input multiple-output (MIMO) antenna system using the metal rims of a mobile phone without any structural interruption on the long edge frames is proposed. Instead of traditional
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7bf0478e5b12596aa33a2059704bf332
https://ieeexplore.ieee.org/document/9606918/
https://ieeexplore.ieee.org/document/9606918/
Publikováno v:
AAAI
In this paper, we propose a fully convolutional network-based dense map from voxels to invertible pair of displacement vector fields regarding a template grid for the consistent voxel-wise correspondence. We parameterize the volumetric mapping using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c936a984a5064fe397bef3513cec761
https://doi.org/10.1609/aaai.v34i07.6992
https://doi.org/10.1609/aaai.v34i07.6992