Jing Wu

2.3k total citations
87 papers, 1.4k citations indexed

About

Jing Wu is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Jing Wu has authored 87 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 22 papers in Molecular Biology and 17 papers in Artificial Intelligence. Recurrent topics in Jing Wu's work include Plant Stress Responses and Tolerance (11 papers), Face recognition and analysis (9 papers) and Face and Expression Recognition (8 papers). Jing Wu is often cited by papers focused on Plant Stress Responses and Tolerance (11 papers), Face recognition and analysis (9 papers) and Face and Expression Recognition (8 papers). Jing Wu collaborates with scholars based in China, United Kingdom and United States. Jing Wu's co-authors include Yu‐Kun Lai, Shi‐Xia Liu, Qian Xie, S H Chen, Edwin R. Hancock, William A. P. Smith, Yiming Zhang, Jun Wang, Kai Xu and Jun Zhu and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Molecular and Cellular Biology.

In The Last Decade

Jing Wu

83 papers receiving 1.4k citations

Peers

Jing Wu

CVPR

Yujia Li China

Xufeng Han China

Zhirong Yang Finland

Søren Kaae Sønderby Denmark

T. M. Murali United States

Bailing Zhang China

Min Tan China

Masaki Aono Japan

Wei Zhou China

Yujia Li China

Jing Wu

442 ×0.9

CVPR

475 ×1.2

497 ×2.1

142 ×0.8

29 ×0.2

Citations per year, relative to Jing Wu Jing Wu (= 1×) peers Yujia Li

Countries citing papers authored by Jing Wu

Since Specialization

Citations

This map shows the geographic impact of Jing Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jing Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Wu more than expected).

Fields of papers citing papers by Jing Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jing Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jing Wu. The network helps show where Jing Wu may publish in the future.

Co-authorship network of co-authors of Jing Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Wu. A scholar is included among the top collaborators of Jing Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jing Wu. Jing Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Huo, Jing, et al.. (2024). Towards efficient image and video style transfer via distillation and learnable feature transformation. Computer Vision and Image Understanding. 241. 103947–103947. 3 indexed citations

Wu, Jing, et al.. (2023). Efficient Hierarchical Reinforcement Learning for Mapless Navigation With Predictive Neighbouring Space Scoring. IEEE Transactions on Automation Science and Engineering. 21(4). 5457–5472. 6 indexed citations

Ji, Ze, et al.. (2023). Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective. IEEE Transactions on Cognitive and Developmental Systems. 15(3). 1139–1149. 8 indexed citations

Zhang, Haijun, Yanchao Yuan, Huixian Xing, et al.. (2023). Genome-wide identification and expression analysis of the HVA22 gene family in cotton and functional analysis of GhHVA22E1D in drought and salt tolerance. Frontiers in Plant Science. 14. 1139526–1139526. 11 indexed citations

Pan, Xiaoyong, Hong‐Bin Shen, Kup‐Sze Choi, et al.. (2022). MDGF-MCEC: a multi-view dual attention embedding model with cooperative ensemble learning for CircRNA-disease association prediction. Briefings in Bioinformatics. 23(5). 14 indexed citations

Wang, Yuan‐Yuan, et al.. (2022). The R2R3-MYB transcription factor ThRAX2 recognized a new element MYB-T (CTTCCA) to enhance cadmium tolerance in Tamarix hispida. Plant Science. 329. 111574–111574. 22 indexed citations

Zhou, Wei, Jian‐Gang Ma, Hui Lin, et al.. (2022). Antimicrobial resistance and genomic characterization of Escherichia coli from pigs and chickens in Zhejiang, China. Frontiers in Microbiology. 13. 1018682–1018682. 24 indexed citations

Wu, Jing, Lili Mao, Jincai Tao, et al.. (2022). Dynamic Quantitative Trait Loci Mapping for Plant Height in Recombinant Inbred Line Population of Upland Cotton. Frontiers in Plant Science. 13. 914140–914140. 8 indexed citations

Pan, Xiaoyong, Hong‐Bin Shen, Kup‐Sze Choi, et al.. (2021). circRNA-binding protein site prediction based on multi-view deep learning, subspace learning and multi-view classifier. Briefings in Bioinformatics. 23(1). 20 indexed citations

10.

Ji, Ze, Jing Wu, Yu‐Kun Lai, et al.. (2021). Hierarchical Reinforcement Learning With Universal Policies for Multistep Robotic Manipulation. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4727–4741. 58 indexed citations

11.

Zappalá, Stefano, Jing Wu, Sławomir Kuśmia, et al.. (2021). Full-field MRI measurements of in-vivo positional brain shift reveal the significance of intra-cranial geometry and head orientation for stereotactic surgery. Scientific Reports. 11(1). 17684–17684. 8 indexed citations

12.

Liu, Zhongyuan, Qingjun Xie, Feifei Tang, et al.. (2021). The ThSOS3 Gene Improves the Salt Tolerance of Transgenic Tamarix hispida and Arabidopsis thaliana. Frontiers in Plant Science. 11. 597480–597480. 24 indexed citations

13.

Wang, Xin, et al.. (2019). Discriminative features matter: Multi-layer bilinear pooling for camera localization. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 87. 4 indexed citations

14.

Pan, Yaohua, Zhibin Niu, Jing Wu, & Jiawan Zhang. (2019). InSocialNet: Interactive visual analytics for role-event videos. Computational Visual Media. 5(4). 375–390. 5 indexed citations

15.

Li, Xiaolong, et al.. (2018). Method Based on Floating Car Data and Gradient-Boosted Decision Tree Classification for the Detection of Auxiliary Through Lanes at Intersections. ISPRS International Journal of Geo-Information. 7(8). 317–317. 3 indexed citations

16.

Zhou, Yu, Jing Wu, Wen Xiao, et al.. (2018). Arabidopsis IQM4, a Novel Calmodulin-Binding Protein, Is Involved With Seed Dormancy and Germination in Arabidopsis. Frontiers in Plant Science. 9. 721–721. 21 indexed citations

17.

Sun, Jiayi, Jing Wu, Hong Qian, Bin Liu, & Shiqing Zhang. (2017). [Discussion about Supervision Model of Customized Medical Device].. PubMed. 41(6). 432–435. 1 indexed citations

18.

Yun, Jieun, Antonio Pannuti, Ignacio Espinoza, et al.. (2013). Crosstalk between PKCα and Notch-4 in endocrine-resistant breast cancer cells. Oncogenesis. 2(8). e60–e60. 56 indexed citations

19.

Wu, Jing, William A. P. Smith, & Edwin R. Hancock. (2007). Gender Classification using Shape from Shading. 5 indexed citations

20.

Lowndes, Noel F., Pierre R. Bushel, Laurel Mendelsohn, et al.. (1990). A Short, Highly Repetitive Element in Intron -1 of the Human c-Ha- ras Gene Acts as a Block to Transcriptional Readthrough by a Viral Promoter. Molecular and Cellular Biology. 10(9). 4990–4995. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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