Yan Wu

3.9k total citations · 1 hit paper
231 papers, 2.4k citations indexed

About

Yan Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Yan Wu has authored 231 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computer Vision and Pattern Recognition, 50 papers in Artificial Intelligence and 29 papers in Control and Systems Engineering. Recurrent topics in Yan Wu's work include Advanced Neural Network Applications (22 papers), Advanced Algorithms and Applications (14 papers) and EEG and Brain-Computer Interfaces (13 papers). Yan Wu is often cited by papers focused on Advanced Neural Network Applications (22 papers), Advanced Algorithms and Applications (14 papers) and EEG and Brain-Computer Interfaces (13 papers). Yan Wu collaborates with scholars based in China, United States and Singapore. Yan Wu's co-authors include Xinneng Yang, Feilin Liu, Yujian Mo, Yujun Liao, Junming Zhang, Yuanfang Ren, Jun‐Ming Zhang, Junqiao Zhao, Fuqiang Chen and Yi Luo and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Power Sources.

In The Last Decade

Yan Wu

204 papers receiving 2.4k 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.

Review the state-of-the-art technologies of semantic segmentation based on deep learning

2022 396 citations Yan Wu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yan Wu China	23	626	391	317	235	196	231	2.4k
Weikuan Jia China	31	619 1.0×	684 1.7×	174 0.5×	211 0.9×	103 0.5×	128	3.2k
Kai Huang China	29	642 1.0×	368 0.9×	261 0.8×	713 3.0×	155 0.8×	336	3.6k
Saad Albawi Iraq	8	727 1.2×	753 1.9×	107 0.3×	260 1.1×	99 0.5×	16	2.7k
Bijoy K. Ghosh United States	35	681 1.1×	493 1.3×	181 0.6×	531 2.3×	530 2.7×	212	4.0k
Saad Al-Azawi Iraq	6	736 1.2×	733 1.9×	105 0.3×	274 1.2×	98 0.5×	16	2.6k
Wenjie Yang China	7	927 1.5×	797 2.0×	99 0.3×	347 1.5×	117 0.6×	17	3.1k
Tareq Abed Mohammed Iraq	7	708 1.1×	754 1.9×	96 0.3×	274 1.2×	97 0.5×	18	2.7k
Lei Wei China	25	483 0.8×	169 0.4×	174 0.5×	466 2.0×	181 0.9×	172	2.3k
Chuan‐Yu Chang Taiwan	31	984 1.6×	834 2.1×	114 0.4×	198 0.8×	142 0.7×	228	3.6k

Countries citing papers authored by Yan Wu

Since Specialization

Citations

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

Fields of papers citing papers by Yan Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Wu

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

All Works

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20 of 20 papers shown

1.

Wu, Yan, et al.. (2024). Study on multidimensional emotion recognition fusing dynamic brain network features in EEG signals. Biomedical Signal Processing and Control. 100. 107054–107054. 3 indexed citations

2.

Wang, Wenwen, Lixia Tian, Rui Liu, et al.. (2024). QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii. International Journal of Molecular Sciences. 25(17). 9639–9639. 3 indexed citations

3.

Karanov, Boris, et al.. (2024). On the Robustness of Deep Learning-Aided Symbol Detectors to Varying Conditions and Imperfect Channel Knowledge. TU/e Research Portal. 1–6. 1 indexed citations

4.

Wu, Yan & Zili Zhang. (2023). Refining large knowledge bases using co-occurring information in associated KBs. Frontiers in Physics. 11.

5.

Wen, Kai, et al.. (2021). A machine learning-based surrogate model for the rapid control of piping flow: Application to a natural gas flowmeter calibration system. Journal of Natural Gas Science and Engineering. 98. 104384–104384. 14 indexed citations

6.

Gao, Rui, Cheng Chen, Hang Wang, et al.. (2020). Classification of multicategory edible fungi based on the infrared spectra of caps and stalks. PLoS ONE. 15(8). e0238149–e0238149. 18 indexed citations

7.

Song, Huanhuan, et al.. (2017). Survey of construction of PICC nurses of Shandong province. The Journal of practical nursing. 33(15). 1179–1183. 1 indexed citations

8.

Luo, Yi, Yue Ma, Yan Wu, Hongwei Liu, & Lei Cao. (2016). Full-traveltime inversion. Geophysics. 81(5). R261–R274. 87 indexed citations

9.

Wu, Yan. (2015). Accuracy Optimization of RPC Model Based on Linear Features Control. Remote Sensing Information. 1 indexed citations

10.

Li, Qi, et al.. (2014). The temporal reliability of sound modulates visual detection: An event-related potential study. Neuroscience Letters. 584. 202–207. 5 indexed citations

11.

Chen, Siyuan, Yan Wu, Li Zhu, et al.. (2012). Cutaneous intravascular NK/T cell lymphoma: a case report. Chinese Journal of Dermatology. 45(3). 151–154. 2 indexed citations

12.

Wu, Yan. (2011). Survey on adaptive genetic algorithm based on dynamic invasion. Computer Engineering and Applications Journal. 1 indexed citations

13.

Wu, Yan. (2010). A method of careful lung segmentation based on CT images. Journal of Chongqing University of Posts and Telecommunications. 4 indexed citations

14.

Wu, Yan. (2008). Multi-population univariate marginal distribution algorithm for dynamic optimization problems. Kongzhi yu juece. 2 indexed citations

15.

Tao, Juan, Changzheng Huang, Yan Wu, et al.. (2008). Olmsted syndrome: a case report and review of literature. International Journal of Dermatology. 47(5). 432–437. 21 indexed citations

16.

Wu, Yan & H. Kanamori. (2005). Pd attenuation and its application to earthquake early warning. AGU Fall Meeting Abstracts. 2005. 1 indexed citations

17.

Wu, Yan. (2004). A Novel Neural Network Architecture and Its Learning Algorithm. Jisuanji gongcheng. 1 indexed citations

18.

Wu, Yan. (2002). A Survey of Research Work on Neural Network Generalization and Structure Optimization Algorithms. Jisuanji yingyong yanjiu. 7 indexed citations

19.

Ioup, Juliette W., et al.. (2000). Multilayer MIM inversion of AEM data: Theory and field example. Geophysics. 66(1). 125–136. 2 indexed citations

20.

Wu, Yan, et al.. (1999). A new vertical continuation procedure for airborne electromagnetic field data from the modified image method. Geophysics. 64(5). 1364–1368. 5 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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