Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Zourong Long"'
Publikováno v:
IET Computer Vision, Vol 18, Iss 6, Pp 813-825 (2024)
Abstract Skeleton‐based action recognition has received much attention and achieved remarkable achievements in the field of human action recognition. In time series action prediction for different scales, existing methods mainly focus on attention
Externí odkaz:
https://doaj.org/article/bdd94b3906084304afa8b5d6d0ee3f2e
Autor:
Bosi Wang, Zourong Long, Xinhai Chen, Chenjun Feng, Min Zhao, Dihua Sun, Weiping Wang, Shihao Wang
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
Road surface detection plays a pivotal role in the realm of autonomous vehicle navigation. Contemporary methodologies primarily leverage LiDAR for acquiring three-dimensional data and utilize imagery for chromatic information. However, these approach
Externí odkaz:
https://doaj.org/article/d276cf3657954509871d25e9ec40adc7
Autor:
Xiaojie Lv, Xuezhi Ren, Peng He, Mi Zhou, Zourong Long, Xiaodong Guo, Chengyu Fan, Biao Wei, Peng Feng
Publikováno v:
IEEE Access, Vol 8, Pp 225594-225601 (2020)
The spectral computed tomography (CT) based on photon counting detectors can collect the incident photons with different energy ranges. However, due to the low photon counts in narrow energy bin and the unhomogeneous response problem of detector cell
Externí odkaz:
https://doaj.org/article/c3b264084bb6429a9d0f990904ace660
Autor:
Fengxiao Li, Zourong Long, Peng He, Peng Feng, Xiaodong Guo, Xuezhi Ren, Biao Wei, Mingfu Zhao, Bin Tang
Publikováno v:
IEEE Access, Vol 8, Pp 229132-229140 (2020)
Semantic segmentation networks focus on the scene parsing of an unrestricted open scene. The typical segmentation architectures are stacks consisting of convolutional layers, which are used to extract semantic features. The feature map dimension is s
Externí odkaz:
https://doaj.org/article/02eadafd268442d197417497e69b4609
Autor:
Zourong Long, Peng He, Xiaochuan Wu, Xiaodong Guo, Xuezhi Ren, Mianyi Chen, Jingxuan Gao, Biao Wei, Wenxiang Cong, Peng Feng
Publikováno v:
IEEE Access, Vol 7, Pp 167187-167194 (2019)
The spectral computed tomography (CT) based on photon-counting detector performs energy-dependent image reconstruction of material attenuation coefficients, allowing for effective medical diagnosis and material discrimination. However, the spectral C
Externí odkaz:
https://doaj.org/article/b933794a31ff457f8d06c5d508159963
Publikováno v:
5th International Conference on Computer Information Science and Application Technology (CISAT 2022).
Autor:
Hang Liu, Bin Tang, Zourong Long, Jianxu Wang, Qing Chen, Junfeng Miao, Jinfu Zhang, Mingfu Zhao, Nianbing Zhong, Huan Tang
Publikováno v:
5th International Conference on Computer Information Science and Application Technology (CISAT 2022).
Publikováno v:
5th International Conference on Computer Information Science and Application Technology (CISAT 2022).
Autor:
Ninghui Yang, Bin Tang, Zourong Long, Jianxu Wang, Linfeng Cai, Liyong Dai, Haidong Zheng, Lin Xie, Mingfu Zhao
Publikováno v:
5th International Conference on Computer Information Science and Application Technology (CISAT 2022).
Autor:
Chengyu Fan, Xiaodong Guo, Mi Zhou, Biao Wei, Peng He, Zourong Long, Xuezhi Ren, Xiaojie Lv, Peng Feng
Publikováno v:
IEEE Access, Vol 8, Pp 225594-225601 (2020)
The spectral computed tomography (CT) based on photon counting detectors can collect the incident photons with different energy ranges. However, due to the low photon counts in narrow energy bin and the unhomogeneous response problem of detector cell