Jianhui Yu

792 total citations · 1 hit paper
20 papers, 503 citations indexed

About

Jianhui Yu is a scholar working on Computer Vision and Pattern Recognition, Developmental and Educational Psychology and Computer Science Applications. According to data from OpenAlex, Jianhui Yu has authored 20 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Developmental and Educational Psychology and 5 papers in Computer Science Applications. Recurrent topics in Jianhui Yu's work include Innovative Teaching and Learning Methods (7 papers), Online Learning and Analytics (5 papers) and Online and Blended Learning (4 papers). Jianhui Yu is often cited by papers focused on Innovative Teaching and Learning Methods (7 papers), Online Learning and Analytics (5 papers) and Online and Blended Learning (4 papers). Jianhui Yu collaborates with scholars based in China, Australia and Taiwan. Jianhui Yu's co-authors include Yang Song, Weidong Cai, Chaoyi Zhang, Changqin Huang, Tiange Xiang, Zhongmei Han, Tao He, Ming Li, Wenbin Qian and Wenhao Shu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and International Journal of Environmental Research and Public Health.

In The Last Decade

Jianhui Yu

19 papers receiving 484 citations

Hit Papers

Walk in the Cloud: Learning Curves for Point Clouds Shape... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jianhui Yu China 12 167 130 103 87 85 20 503
Zhongmei Han China 14 38 0.2× 66 0.5× 17 0.2× 133 1.5× 190 2.2× 25 634
Xizhe Wang China 10 27 0.2× 128 1.0× 17 0.2× 45 0.5× 138 1.6× 20 446
Qionghao Huang China 15 34 0.2× 211 1.6× 17 0.2× 34 0.4× 259 3.0× 34 637
Daniel Duckworth United States 10 47 0.3× 174 1.3× 10 0.1× 238 2.7× 145 1.7× 20 816
Roberto Vivó Spain 8 19 0.1× 121 0.9× 5 0.0× 89 1.0× 23 0.3× 37 354
Rosemary Michelle Simpson United States 9 12 0.1× 182 1.4× 21 0.2× 15 0.2× 35 0.4× 20 399
Eike Falk Anderson United Kingdom 10 6 0.0× 240 1.8× 82 0.8× 35 0.4× 88 1.0× 51 587
Kelvin Sung United States 14 44 0.3× 145 1.1× 6 0.1× 26 0.3× 32 0.4× 59 495
Eric M. Hoffert United States 9 152 0.9× 258 2.0× 17 0.2× 16 0.2× 13 0.2× 11 448
Zhutian Chen United States 16 24 0.1× 474 3.6× 20 0.2× 3 0.0× 185 2.2× 34 670

Countries citing papers authored by Jianhui Yu

Since Specialization
Citations

This map shows the geographic impact of Jianhui Yu'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 Jianhui Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianhui Yu more than expected).

Fields of papers citing papers by Jianhui Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jianhui Yu. 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 Jianhui Yu. The network helps show where Jianhui Yu may publish in the future.

Co-authorship network of co-authors of Jianhui Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Jianhui Yu. A scholar is included among the top collaborators of Jianhui Yu 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 Jianhui Yu. Jianhui Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yu, Jianhui. (2025). Analyzing Learning Sentiments on a MOOC Discussion Forum Through Epistemic Network Analysis. The International Review of Research in Open and Distributed Learning. 26(1). 197–215.
2.
Xu, Kang, et al.. (2025). SOH estimation of lithium battery based on improved quantum particle swarm optimization hybrid neural network. Ionics. 31(8). 7863–7880. 1 indexed citations
3.
Huang, Changqin, Jianhui Yu, Fei Wu, Yi Wang, & Nian‐Shing Chen. (2024). Uncovering emotion sequence patterns in different interaction groups using deep learning and sequential pattern mining. Journal of Computer Assisted Learning. 40(4). 1777–1790. 3 indexed citations
4.
Shu, Wenhao, et al.. (2023). Neighbourhood discernibility degree-based semisupervised feature selection for partially labelled mixed-type data with granular ball. Applied Intelligence. 53(19). 22467–22487. 5 indexed citations
5.
Shu, Wenhao, et al.. (2022). Semi-supervised feature selection for partially labeled mixed-type data based on multi-criteria measure approach. International Journal of Approximate Reasoning. 153. 258–279. 11 indexed citations
6.
Shu, Wenhao, et al.. (2022). Information gain-based semi-supervised feature selection for hybrid data. Applied Intelligence. 53(6). 7310–7325. 26 indexed citations
8.
Shu, Wenhao, et al.. (2022). Information granularity-based incremental feature selection for partially labeled hybrid data. Intelligent Data Analysis. 26(1). 33–56. 4 indexed citations
9.
Huang, Changqin, et al.. (2021). Exploring the Relationships between Achievement Goals, Community Identification and Online Collaborative Reflection: A Deep Learning and Bayesian Approach. SHILAP Revista de lepidopterología. 18 indexed citations
10.
Xiang, Tiange, Chaoyi Zhang, Yang Song, Jianhui Yu, & Weidong Cai. (2021). Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 895–904. 177 indexed citations breakdown →
12.
Zhang, Chaoyi, Jianhui Yu, Yang Song, & Weidong Cai. (2021). Exploiting Edge-Oriented Reasoning for 3D Point-based Scene Graph Analysis. UNSWorks (University of New South Wales, Sydney, Australia). 9700–9710. 39 indexed citations
13.
Han, Zhongmei, Changqin Huang, Jianhui Yu, & Chin‐Chung Tsai. (2021). Identifying patterns of epistemic emotions with respect to interactions in massive online open courses using deep learning and social network analysis. Computers in Human Behavior. 122. 106843–106843. 38 indexed citations
14.
Yu, Jianhui, Chaoyi Zhang, Yang Song, & Weidong Cai. (2021). ICE-GAN: Identity-Aware and Capsule-Enhanced GAN with Graph-Based Reasoning for Micro-Expression Recognition and Synthesis. 1–8. 16 indexed citations
16.
Yu, Jianhui, et al.. (2020). ICE-GAN: Identity-aware and Capsule-Enhanced GAN for Micro-Expression Recognition and Synthesis.. 14 indexed citations
17.
Yu, Jianhui, Changqin Huang, Zhongmei Han, Tao He, & Ming Li. (2020). Investigating the Influence of Interaction on Learning Persistence in Online Settings: Moderation or Mediation of Academic Emotions?. International Journal of Environmental Research and Public Health. 17(7). 2320–2320. 77 indexed citations
18.
Fang, Junbin, Yunhan Luo, Jianhui Yu, et al.. (2018). Research and application of binarization algorithm of QR code image under complex illumination. Journal of Applied Optics. 39(5). 64–70. 4 indexed citations
19.
Dang, Yunxiao, Wenzhong Zhang, Jianhui Yu, Chen Li, & Dongsheng Zhan. (2014). Residents' subjective well-being and influencing factors in Beijing. 33(10). 1312–1321. 4 indexed citations
20.
Xue, Andy Yuan, Rui Zhang, Yu Zheng, et al.. (2013). DesTeller. Proceedings of the VLDB Endowment. 6(12). 1198–1201. 25 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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