Haiping Yu

574 total citations
14 papers, 484 citations indexed

About

Haiping Yu is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence. According to data from OpenAlex, Haiping Yu has authored 14 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Information Systems and 4 papers in Artificial Intelligence. Recurrent topics in Haiping Yu's work include Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (3 papers) and Advanced Vision and Imaging (2 papers). Haiping Yu is often cited by papers focused on Recommender Systems and Techniques (7 papers), Advanced Graph Neural Networks (3 papers) and Advanced Vision and Imaging (2 papers). Haiping Yu collaborates with scholars based in China and France. Haiping Yu's co-authors include Yiteng Pan, Fazhi He, Fazhi He, Xiao Chen, Kang Li, Xiaohong Chen, Kang Li, Haoran Li, Geng Chen and Yuquan Zhu and has published in prestigious journals such as IEEE Access, Neurocomputing and Neural Computing and Applications.

In The Last Decade

Haiping Yu

12 papers receiving 468 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haiping Yu China 9 222 195 178 61 26 14 484
David F. Barrero Spain 12 93 0.4× 167 0.9× 93 0.5× 57 0.9× 13 0.5× 41 354
Jinlin Chen China 12 105 0.5× 151 0.8× 181 1.0× 113 1.9× 33 1.3× 57 535
Yuxin Mao China 14 140 0.6× 157 0.8× 111 0.6× 181 3.0× 15 0.6× 66 554
Chang‐Sung Jeong South Korea 12 219 1.0× 97 0.5× 94 0.5× 166 2.7× 31 1.2× 69 535
Zhenguo Yang China 15 262 1.2× 295 1.5× 146 0.8× 61 1.0× 14 0.5× 60 613
Mingxuan Sun United States 14 219 1.0× 205 1.1× 144 0.8× 132 2.2× 7 0.3× 53 659
Rongfei Jia China 9 364 1.6× 289 1.5× 104 0.6× 37 0.6× 19 0.7× 18 739
M. M. Raghuwanshi India 10 121 0.5× 248 1.3× 72 0.4× 51 0.8× 14 0.5× 62 496
Kun-Ming Yu Taiwan 13 126 0.6× 153 0.8× 161 0.9× 141 2.3× 49 1.9× 64 573

Countries citing papers authored by Haiping Yu

Since Specialization
Citations

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

Fields of papers citing papers by Haiping Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiping Yu

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

All Works

14 of 14 papers shown
1.
Yuan, Ling, et al.. (2021). Deep context interaction network based on attention mechanism for click-through rate prediction. Journal of Intelligent & Fuzzy Systems. 41(6). 6899–6914.
2.
Yu, Haiping. (2020). Application of Large Data Technology in Financial Credit Risk Prediction of Internet of Things. Solid State Technology. 63(4). 6811–6818. 1 indexed citations
3.
Pan, Yiteng, Fazhi He, & Haiping Yu. (2020). Learning social representations with deep autoencoder for recommender system. World Wide Web. 23(4). 2259–2279. 123 indexed citations
4.
Pan, Yiteng, Fazhi He, Haiping Yu, & Haoran Li. (2019). Learning adaptive trust strength with user roles of truster and trustee for trust-aware recommender systems. Applied Intelligence. 50(2). 314–327. 27 indexed citations
5.
Pan, Yiteng, Fazhi He, & Haiping Yu. (2019). A correlative denoising autoencoder to model social influence for top-N recommender system. Frontiers of Computer Science. 14(3). 71 indexed citations
6.
Chen, Xiao, Fazhi He, & Haiping Yu. (2018). A matting method based on full feature coverage. Multimedia Tools and Applications. 78(9). 11173–11201. 50 indexed citations
7.
Li, Kang, Fazhi He, Haiping Yu, & Xiaohong Chen. (2018). A parallel and robust object tracking approach synthesizing adaptive Bayesian learning and improved incremental subspace learning. Frontiers of Computer Science. 13(5). 1116–1135. 52 indexed citations
8.
Pan, Yiteng, Fazhi He, & Haiping Yu. (2018). An Adaptive Method to Learn Directive Trust Strength for Trust-aware Recommender Systems. 10–16. 3 indexed citations
9.
Pan, Yiteng, Fazhi He, & Haiping Yu. (2018). A novel Enhanced Collaborative Autoencoder with knowledge distillation for top-N recommender systems. Neurocomputing. 332. 137–148. 82 indexed citations
10.
Li, Kang, Fazhi He, & Haiping Yu. (2018). Robust Visual Tracking Based on Convolutional Features with Illumination and Occlusion Handing. Journal of Computer Science and Technology. 33(1). 223–236. 48 indexed citations
11.
Pan, Yiteng, Fazhi He, & Haiping Yu. (2017). Trust-aware Collaborative Denoising Auto-Encoder for Top-N Recommendation. arXiv (Cornell University). 11 indexed citations
12.
Chen, Xiao, Fazhi He, & Haiping Yu. (2017). A Three-Stage Matting Method. IEEE Access. 5. 27732–27739.
13.
Yu, Haiping, et al.. (2011). The Presence of Conspecific Decoys Enhances the Attractiveness of an NaCl Resource to the Yellow-Spined Locust,Ceracris kiangsu. Journal of Insect Science. 11(45). 1–9. 3 indexed citations
14.
Zhu, Yuquan, et al.. (2010). Dynamic weighting ensemble classifiers based on cross-validation. Neural Computing and Applications. 20(3). 309–317. 13 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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2026