Jin Yu

873 total citations
21 papers, 512 citations indexed

About

Jin Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Jin Yu has authored 21 papers receiving a total of 512 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 3 papers in Computational Mechanics. Recurrent topics in Jin Yu's work include Optical measurement and interference techniques (5 papers), Image and Object Detection Techniques (4 papers) and Machine Learning and Algorithms (3 papers). Jin Yu is often cited by papers focused on Optical measurement and interference techniques (5 papers), Image and Object Detection Techniques (4 papers) and Machine Learning and Algorithms (3 papers). Jin Yu collaborates with scholars based in China, Australia and Singapore. Jin Yu's co-authors include Nicol N. Schraudolph, Tat-Jun Chin, David Suter, Simon Günter, Trung Pham, Zonghua Zhang, Nan Gao, Zhaozong Meng, Douglas Aberdeen and Chao Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Optics Express and Pattern Recognition.

In The Last Decade

Jin Yu

20 papers receiving 483 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jin Yu China	11	295	196	89	78	54	21	512
Qingshan Xu China	10	341 1.2×	137 0.7×	36 0.4×	84 1.1×	118 2.2×	29	590
Doron Mintz United States	6	359 1.2×	59 0.3×	40 0.4×	114 1.5×	21 0.4×	11	522
Jiahao Pang Hong Kong	15	857 2.9×	162 0.8×	221 2.5×	106 1.4×	61 1.1×	44	1.1k
Kumar S. Ray India	14	326 1.1×	336 1.7×	91 1.0×	61 0.8×	10 0.2×	73	778
Keshu Zhang United States	15	336 1.1×	512 2.6×	37 0.4×	178 2.3×	19 0.4×	43	1.0k
Jianfeng Zhang China	12	539 1.8×	98 0.5×	41 0.5×	73 0.9×	25 0.5×	50	705
Ioannis Mitliagkas United States	12	349 1.2×	269 1.4×	263 3.0×	26 0.3×	89 1.6×	27	760
Jiye Qian China	10	181 0.6×	57 0.3×	43 0.5×	84 1.1×	7 0.1×	34	483
Bogdan Savchynskyy Germany	11	366 1.2×	200 1.0×	57 0.6×	88 1.1×	36 0.7×	23	552
Ting Hu China	11	146 0.5×	223 1.1×	242 2.7×	37 0.5×	79 1.5×	49	561

Countries citing papers authored by Jin Yu

Since Specialization

Citations

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

Fields of papers citing papers by Jin Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jin Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Jin Yu. A scholar is included among the top collaborators of Jin 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 Jin Yu. Jin Yu 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

Yu, Jin, et al.. (2024). Artificial intelligence and glaucoma: a lucid and comprehensive review. Frontiers in Medicine. 11. 1423813–1423813. 1 indexed citations

Zhang, Shengyu, Kun Kuang, Fuli Feng, et al.. (2023). SLED: Structure Learning based Denoising for Recommendation. ACM Transactions on Information Systems. 42(2). 1–31. 7 indexed citations

Yu, Jin, Zonghua Zhang, Feng Gao, et al.. (2022). High-accuracy camera calibration method based on coded concentric ring center extraction. Optics Express. 30(23). 42454–42454. 15 indexed citations

Tan, Ziqi, Shengyu Zhang, Jin Yu, et al.. (2022). Uncovering Causal Effects of Online Short Videos on Consumer Behaviors. 997–1006. 4 indexed citations

Yu, Jin, et al.. (2021). Data-free Knowledge Distillation via Adversarial. 447–451. 1 indexed citations

Zhang, Shengyu, Tan Wang, Kun Kuang, et al.. (2021). DeVLBert: Out-of-distribution Visio-Linguistic Pretraining with Causality. 1744–1747.

Yu, Jin, Nan Gao, Zhaozong Meng, & Zonghua Zhang. (2021). High-accuracy projector calibration method for fringe projection profilometry considering perspective transformation. Optics Express. 29(10). 15053–15053. 25 indexed citations

Yu, Jin, et al.. (2020). Efficient Architecture Paradigm for Deep Learning Inference as a Service. 12. 1–8. 1 indexed citations

Yu, Jin, Nan Gao, Zhaozong Meng, & Zonghua Zhang. (2020). A three-dimensional measurement system calibration method based on red/blue orthogonal fringe projection. Optics and Lasers in Engineering. 139. 106506–106506. 10 indexed citations

10.

Yu, Jin, Nan Gao, Zonghua Zhang, & Zhaozong Meng. (2020). High Sensitivity Fringe Projection Profilometry Combining Optimal Fringe Frequency and Optimal Fringe Direction. Optics and Lasers in Engineering. 129. 106068–106068. 22 indexed citations

11.

Yu, Jin & Ying Li. (2019). Neural Network Approximation for Nonlinear Partial Differential Equations with Quasi-Newton Optimization and Piecewise Strategy. 1643–1647. 1 indexed citations

12.

Chen, Chao, Jin Yu, Nan Gao, & Zonghua Zhang. (2019). High accuracy 3D calibration method of phase calculation-based fringe projection system by using LCD screen considering refraction error. Optics and Lasers in Engineering. 126. 105870–105870. 23 indexed citations

13.

Pham, Trung, Tat-Jun Chin, Jin Yu, & David Suter. (2014). The Random Cluster Model for Robust Geometric Fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(8). 1658–1671. 85 indexed citations

14.

Pham, Trung, Tat-Jun Chin, Jin Yu, & David Suter. (2012). The Random Cluster Model for robust geometric fitting. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 710–717. 13 indexed citations

15.

Chin, Tat-Jun, et al.. (2012). Mode seeking over permutations for rapid geometric model fitting. Pattern Recognition. 46(1). 257–271. 16 indexed citations

16.

Pham, Trung, Tat-Jun Chin, Jin Yu, & David Suter. (2011). Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 24. 540–548. 12 indexed citations

17.

Chin, Tat-Jun, et al.. (2011). Dynamic and hierarchical multi-structure geometric model fitting. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 89 indexed citations

18.

Petterson, James, Tibério S. Caetano, Julian McAuley, & Jin Yu. (2009). Exponential Family Graph Matching and Ranking. ArXiv.org. 22. 1455–1463. 7 indexed citations

19.

Schraudolph, Nicol N., Jin Yu, & Simon Günter. (2007). A stochastic quasi-Newton method for online convex optimization. ANU Open Research (Australian National University). 436–443. 155 indexed citations

20.

Yu, Jin, Douglas Aberdeen, & Nicol N. Schraudolph. (2005). Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation. Neural Information Processing Systems. 18. 1185–1192. 18 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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