Ruomei Yan

801 total citations · 1 hit paper
7 papers, 631 citations indexed

About

Ruomei Yan is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Biomedical Engineering. According to data from OpenAlex, Ruomei Yan has authored 7 papers receiving a total of 631 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Media Technology and 2 papers in Biomedical Engineering. Recurrent topics in Ruomei Yan's work include Image and Signal Denoising Methods (6 papers), Advanced Image Fusion Techniques (5 papers) and Image Processing Techniques and Applications (3 papers). Ruomei Yan is often cited by papers focused on Image and Signal Denoising Methods (6 papers), Advanced Image Fusion Techniques (5 papers) and Image Processing Techniques and Applications (3 papers). Ruomei Yan collaborates with scholars based in United Kingdom, China and Hong Kong. Ruomei Yan's co-authors include Ling Shao, Yan Liu, Xuelong Li, J. Klijn, Li Liu, Wenxing Hu and Lixin Guan and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Cybernetics and Signal Processing.

In The Last Decade

Ruomei Yan

6 papers receiving 617 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms

2013 303 citations Ling Shao, Ruomei Yan et al. IEEE Transactions on Cybernetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ruomei Yan United Kingdom	6	559	345	88	50	35	7	631
Jiangxin Dong China	16	735 1.3×	443 1.3×	30 0.3×	44 0.9×	37 1.1×	26	845
A.J. Patti United States	11	761 1.4×	391 1.1×	77 0.9×	21 0.4×	22 0.6×	24	844
Zhe Hu United States	16	1.4k 2.4×	860 2.5×	74 0.8×	36 0.7×	20 0.6×	18	1.4k
Soheil Darabi United States	8	915 1.6×	186 0.5×	94 1.1×	48 1.0×	13 0.4×	11	984
Mauricio Delbracio United States	10	609 1.1×	258 0.7×	28 0.3×	26 0.5×	29 0.8×	25	696
M.K. Ozkan United States	8	519 0.9×	230 0.7×	62 0.7×	20 0.4×	20 0.6×	11	576
Meng Chang China	5	347 0.6×	150 0.4×	51 0.6×	21 0.4×	42 1.2×	12	495
Pablo Arias France	11	427 0.8×	156 0.5×	73 0.8×	33 0.7×	24 0.7×	34	507
Ramsin Khoshabeh United States	8	329 0.6×	150 0.4×	99 1.1×	75 1.5×	9 0.3×	12	462

Countries citing papers authored by Ruomei Yan

Since Specialization

Citations

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

Fields of papers citing papers by Ruomei Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruomei Yan

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

All Works

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7 of 7 papers shown

1.

Hu, Wenxing, et al.. (2025). An ensemble deep learning framework for multi-class LncRNA subcellular localization with innovative encoding strategy. BMC Biology. 23(1). 47–47.

2.

Yan, Ruomei & Ling Shao. (2016). Blind Estimation of Blur Kernels and Parameters from a Single Image. IEEE Transactions on Image Processing. 25(4). 1–1. 98 indexed citations

3.

Shao, Ling, Ruomei Yan, Xuelong Li, & Yan Liu. (2013). From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms. IEEE Transactions on Cybernetics. 44(7). 1001–1013. 303 indexed citations breakdown →

4.

Yan, Ruomei & Ling Shao. (2013). Image Blur Classification and Parameter Identification Using Two-stage Deep Belief Networks. UEA Digital Repository (University of East Anglia). 70.1–70.11. 20 indexed citations

5.

Yan, Ruomei, Ling Shao, Li Liu, & Yan Liu. (2013). Natural image denoising using evolved local adaptive filters. Signal Processing. 103. 36–44. 24 indexed citations

6.

Yan, Ruomei, Ling Shao, & Yan Liu. (2013). Nonlocal Hierarchical Dictionary Learning Using Wavelets for Image Denoising. IEEE Transactions on Image Processing. 22(12). 4689–4698. 146 indexed citations

7.

Yan, Ruomei, et al.. (2012). Improved Nonlocal Means Based on Pre-Classification and Invariant Block Matching. Journal of Display Technology. 8(4). 212–218. 40 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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