Zoekresultaten - Zejun Wang

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  1. 1

    Molecular Mechanisms of Cell-to-Cell Transmission in Human Herpesviruses door Liyuan Yan, Jing Guo, Yinan Zhong, Jiangbo Wei, Zejun Wang

    Gepubliceerd in 2025-05-01

    Members of the family <i>Orthoherpesviridae</i> employs two distinct transmission modes: free virion release and cell-to-cell transmission. The latter enables immune evasion through multiple mechanisms, facilitating infections in skin, mucosa, and neural tissues. This review synthesizes...

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  2. 2

    Harvesting asymmetric steering via non-identical detectors door Shu-Min Wu, Rui-Di Wang, Xiao-Li Huang, Zejun Wang

    Gepubliceerd in 2025-06-01

    Abstract We investigate asymmetric steering harvesting phenomenon involving two non-identical inertial detectors with different energy gaps, which interact locally with vacuum massless scalar fields. Our study assumes that the energy gap of detector B exceeds that of detector A. It is shown that $$A...

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  3. 3

    Identification of fresh leaves of Anji White Tea: S-YOLOv10-ASI algorithm fusing asymptotic feature pyra-mid network. door Chunhua Yang, Wenxia Yuan, Qiang Zhao, Zejun Wang, Bowu Song, Xianqiu Dong, Yuandong Xiao, Shihao Zhang, Baijuan Wang

    Gepubliceerd in 2025-01-01

    This study proposes the S-YOLOv10-ASI algorithm to improve the accuracy of tea identification and harvesting by robots, integrating a slice-assisted super-reasoning technique. The algorithm improves the partial structure of the YOLOv10 network through space-to-depth convolution. The Progressive Feat...

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  4. 4

    Intelligent Identification of Tea Plant Seedlings Under High-Temperature Conditions via YOLOv11-MEIP Model Based on Chlorophyll Fluorescence Imaging door Chun Wang, Zejun Wang, Lijiao Chen, Weihao Liu, Xinghua Wang, Zhiyong Cao, Jinyan Zhao, Man Zou, Hongxu Li, Wenxia Yuan, Baijuan Wang

    Gepubliceerd in 2025-06-01

    To achieve an efficient, non-destructive, and intelligent identification of tea plant seedlings under high-temperature stress, this study proposes an improved YOLOv11 model based on chlorophyll fluorescence imaging technology for intelligent identification. Using tea plant seedlings under varying de...

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