Yan Wu

2.4k total citations
141 papers, 1.8k citations indexed

About

Yan Wu is a scholar working on Aerospace Engineering, Media Technology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yan Wu has authored 141 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Aerospace Engineering, 43 papers in Media Technology and 39 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yan Wu's work include Synthetic Aperture Radar (SAR) Applications and Techniques (53 papers), Advanced SAR Imaging Techniques (50 papers) and Remote-Sensing Image Classification (35 papers). Yan Wu is often cited by papers focused on Synthetic Aperture Radar (SAR) Applications and Techniques (53 papers), Advanced SAR Imaging Techniques (50 papers) and Remote-Sensing Image Classification (35 papers). Yan Wu collaborates with scholars based in China, Singapore and Algeria. Yan Wu's co-authors include Ming Li, Peng Zhang, Wanying Song, Wenkai Liang, Yice Cao, Lu Jia, Jianwei Fan, Lei Zuo, Hongmeng Chen and Ming Li and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Yan Wu

133 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yan Wu China 24 1.0k 671 570 248 224 141 1.8k
Deliang Xiang China 29 1.3k 1.2× 731 1.1× 751 1.3× 216 0.9× 324 1.4× 107 2.1k
Bin Lei China 21 1.0k 1.0× 559 0.8× 719 1.3× 273 1.1× 364 1.6× 97 2.1k
Zongxu Pan China 24 1.2k 1.1× 739 1.1× 978 1.7× 292 1.2× 397 1.8× 79 2.2k
Lingjun Zhao China 19 844 0.8× 364 0.5× 793 1.4× 226 0.9× 208 0.9× 68 1.6k
Xiaorui Ma China 27 542 0.5× 962 1.4× 662 1.2× 329 1.3× 302 1.3× 63 2.2k
Gui Gao China 25 1.7k 1.7× 447 0.7× 616 1.1× 130 0.5× 256 1.1× 123 2.3k
Gong Zhang China 24 989 1.0× 317 0.5× 364 0.6× 304 1.2× 156 0.7× 230 2.2k
Shunping Xiao China 25 1.6k 1.6× 281 0.4× 362 0.6× 255 1.0× 224 1.0× 162 2.2k
Gongjian Wen China 27 1.3k 1.2× 402 0.6× 824 1.4× 399 1.6× 433 1.9× 114 2.4k

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

20 of 20 papers shown
1.
Wu, Yan, et al.. (2024). A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 17637–17650. 2 indexed citations
2.
Song, Wanying, et al.. (2024). Remote Sensing Scene Classification Based on Semantic-Aware Fusion Network. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 7 indexed citations
3.
Wu, Yan, et al.. (2024). Multifeature Alignment and Matching Network for SAR and Optical Image Registration. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 352–367.
4.
Marchesi, Serena, Davide De Tommaso, Kyveli Kompatsiari, Yan Wu, & Agnieszka Wykowska. (2024). Tools and methods to study and replicate experiments addressing human social cognition in interactive scenarios. Behavior Research Methods. 56(7). 7543–7560. 2 indexed citations
5.
Li, Ming, et al.. (2023). Difference-guided multiscale graph convolution network for unsupervised change detection in PolSAR images. Neurocomputing. 555. 126611–126611. 8 indexed citations
6.
Wu, Yan, et al.. (2023). The influences of working memory updating on word association effects and thematic role assignment during sentence processing. Neuropsychologia. 184. 108547–108547. 1 indexed citations
7.
Wu, Yan, et al.. (2023). Intra- and Inter-Modal Graph Attention Network and Contrastive Learning for SAR and Optical Image Registration. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–16. 7 indexed citations
8.
Song, Wanying, et al.. (2023). HDTFF-Net: Hierarchical Deep Texture Features Fusion Network for High-Resolution Remote Sensing Scene Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 7327–7342. 12 indexed citations
9.
Song, Wanying, et al.. (2022). RF-HoDRF: High-Order Hybrid Discriminative Random Field Improved by Two-Layer Random Forest for SAR Image Change Detection. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 1 indexed citations
10.
Zhang, Peng, et al.. (2021). PolSAR Image Classification Using Hybrid Conditional Random Fields Model Based on Complex-Valued 3-D CNN. IEEE Transactions on Aerospace and Electronic Systems. 57(3). 1713–1730. 21 indexed citations
11.
Zhang, Peng, et al.. (2020). High-Order Triplet CRF-PCANet for Unsupervised Segmentation of Nonstationary SAR Image. IEEE Transactions on Geoscience and Remote Sensing. 59(10). 8433–8454. 7 indexed citations
12.
Song, Wanying, Yan Wu, & Xiaoyu Xiao. (2020). Nonstationary PolSAR Image Classification by Deep-Features-Based High-Order Triple Discriminative Random Field. IEEE Geoscience and Remote Sensing Letters. 18(8). 1406–1410. 6 indexed citations
13.
Song, Wanying, Yan Wu, & Ping Guo. (2020). Composite Kernel and Hybrid Discriminative Random Field Model Based on Feature Fusion for PolSAR Image Classification. IEEE Geoscience and Remote Sensing Letters. 18(6). 1069–1073. 12 indexed citations
14.
Song, Wanying, et al.. (2019). Superpixel-Based Hybrid Discriminative Random Field for Fast PolSAR Image Classification. IEEE Access. 7. 24547–24558. 3 indexed citations
15.
Li, Ming, et al.. (2019). Complex-Valued 3-D Convolutional Neural Network for PolSAR Image Classification. IEEE Geoscience and Remote Sensing Letters. 17(6). 1022–1026. 68 indexed citations
16.
Song, Wanying, Ming Li, Peng Zhang, & Yan Wu. (2019). Fuzziness Modeling of Polarized Scattering Mechanisms and PolSAR Image Classification Using Fuzzy Triplet Discriminative Random Fields. IEEE Transactions on Geoscience and Remote Sensing. 57(7). 4980–4993. 10 indexed citations
17.
Chen, Hongmeng, et al.. (2017). Cross-Range Resolution Enhancement for DBS Imaging in a Scan Mode Using Aperture-Extrapolated Sparse Representation. IEEE Geoscience and Remote Sensing Letters. 14(9). 1459–1463. 14 indexed citations
18.
Song, Wanying, et al.. (2017). Mixture WG $\Gamma$ -MRF Model for PolSAR Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 56(2). 905–920. 31 indexed citations
19.
Wu, Yan, et al.. (2014). RADARSAT-2 Image Quality and Calibration Update. 1–4. 20 indexed citations
20.
Wu, Yan. (2002). Research on Characteristics of Noise Interference in SAR Image. 1 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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