Wanxuan Lu

763 total citations · 2 hit papers
23 papers, 499 citations indexed

About

Wanxuan Lu is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Wanxuan Lu has authored 23 papers receiving a total of 499 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 12 papers in Media Technology and 4 papers in Artificial Intelligence. Recurrent topics in Wanxuan Lu's work include Remote-Sensing Image Classification (12 papers), Advanced Image and Video Retrieval Techniques (10 papers) and Advanced Neural Network Applications (8 papers). Wanxuan Lu is often cited by papers focused on Remote-Sensing Image Classification (12 papers), Advanced Image and Video Retrieval Techniques (10 papers) and Advanced Neural Network Applications (8 papers). Wanxuan Lu collaborates with scholars based in China, Australia and Germany. Wanxuan Lu's co-authors include Xian Sun, Kun Fu, Hongfeng Yu, Peijin Wang, Qibin He, Ruiping Wang, Xuee Rong, Zhujun Yang, Qinglin He and Xiaonan Lü and has published in prestigious journals such as Nature Communications, IEEE Transactions on Geoscience and Remote Sensing and Pattern Recognition.

In The Last Decade

Wanxuan Lu

22 papers receiving 489 citations

Hit Papers

RingMo: A Remote Sensing Foundation Model With Masked Ima... 2022 2026 2023 2024 2022 2025 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wanxuan Lu China 9 235 226 108 68 65 23 499
Xianping Ma China 10 315 1.3× 264 1.2× 88 0.8× 38 0.6× 65 1.0× 28 551
Qibin He China 8 311 1.3× 302 1.3× 119 1.1× 127 1.9× 59 0.9× 15 631
Yuxi Sun China 10 289 1.2× 234 1.0× 91 0.8× 71 1.0× 49 0.8× 25 606
Corneliu Octavian Dumitru Germany 13 251 1.1× 216 1.0× 129 1.2× 197 2.9× 70 1.1× 49 611
Xuee Rong China 8 217 0.9× 328 1.5× 143 1.3× 43 0.6× 31 0.5× 14 504
Yuxuan Li China 5 198 0.8× 175 0.8× 73 0.7× 51 0.8× 31 0.5× 12 443
Xiaochong Tong China 11 132 0.6× 168 0.7× 48 0.4× 101 1.5× 82 1.3× 49 472
Xizhe Xue China 7 193 0.8× 169 0.7× 88 0.8× 57 0.8× 38 0.6× 13 461
Chenyang Liu China 13 342 1.5× 389 1.7× 143 1.3× 51 0.8× 56 0.9× 23 836
Laila Bashmal Saudi Arabia 10 332 1.4× 345 1.5× 181 1.7× 42 0.6× 40 0.6× 17 701

Countries citing papers authored by Wanxuan Lu

Since Specialization
Citations

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

Fields of papers citing papers by Wanxuan Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanxuan Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Wanxuan Lu. A scholar is included among the top collaborators of Wanxuan Lu 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 Wanxuan Lu. Wanxuan Lu 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.
Li, Qiang, Wei Zhang, Wanxuan Lu, & Qi Wang. (2025). Multibranch Mutual-Guiding Learning for Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–10. 17 indexed citations breakdown →
2.
Pan, Xinyu, Chen Zang, Wanxuan Lu, Guiyuan Jiang, & Qian Sun. (2025). FSFF-Net: A Frequency-Domain Feature and Spatial-Domain Feature Fusion Network for Hyperspectral Image Classification. Electronics. 14(11). 2234–2234. 1 indexed citations
3.
Zang, Chen, et al.. (2025). DB-MFENet: A Dual-Branch Multi-Frequency Feature Enhancement Network for Hyperspectral Image Classification. Remote Sensing. 17(8). 1458–1458. 1 indexed citations
4.
Lu, Wanxuan, et al.. (2024). TEA: A Training-Efficient Adapting Framework for Tuning Foundation Models in Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–18. 2 indexed citations
5.
Lu, Wanxuan, et al.. (2024). SFTformer: A Spatial-Frequency-Temporal Correlation-Decoupling Transformer for Radar Echo Extrapolation. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 5 indexed citations
6.
Su, Nan, Zilong Zhao, Yiming Yan, et al.. (2024). MMPW-Net: Detection of Tiny Objects in Aerial Imagery Using Mixed Minimum Point-Wasserstein Distance. Remote Sensing. 16(23). 4485–4485. 4 indexed citations
7.
Yu, Hongfeng, et al.. (2024). Attention-Based Contrastive Learning for Few-Shot Remote Sensing Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–17. 11 indexed citations
8.
Lu, Wanxuan, et al.. (2024). TAFormer: A Unified Target-Aware Transformer for Video and Motion Joint Prediction in Aerial Scenes. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–16. 3 indexed citations
9.
Yu, Hongfeng, et al.. (2024). AiRs: Adapter in Remote Sensing for Parameter-Efficient Transfer Learning. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–18. 16 indexed citations
10.
Lu, Wanxuan, et al.. (2024). Dynamic and Adaptive Self-Training for Semi-Supervised Remote Sensing Image Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 7 indexed citations
11.
Zheng, Xiangtao, et al.. (2024). Advancements in cross-domain remote sensing scene interpretation. Journal of Image and Graphics. 29(6). 1730–1746. 2 indexed citations
12.
Yu, Hongfeng, et al.. (2023). A Light-Weighted Hypergraph Neural Network for Multimodal Remote Sensing Image Retrieval. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 2690–2702. 8 indexed citations
13.
Yao, Fanglong, Wanxuan Lu, Hongfeng Yu, et al.. (2023). RingMo-Sense: Remote Sensing Foundation Model for Spatiotemporal Prediction via Spatiotemporal Evolution Disentangling. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–21. 23 indexed citations
14.
Sun, Xian, Fei Qin, Hongfeng Yu, et al.. (2023). Revealing influencing factors on global waste distribution via deep-learning based dumpsite detection from satellite imagery. Nature Communications. 14(1). 1444–1444. 61 indexed citations
15.
Fu, Kun, et al.. (2023). A Comprehensive Survey and Assumption of Remote Sensing Foundation Modal. National Remote Sensing Bulletin. 0(0). 1–13. 1 indexed citations
16.
Zhang, Lili, Wanxuan Lu, Jinming Zhang, & Hongqi Wang. (2022). A Semisupervised Convolution Neural Network for Partial Unlabeled Remote-Sensing Image Segmentation. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 7 indexed citations
17.
Yu, Hongfeng, Fanglong Yao, Wanxuan Lu, et al.. (2022). Text-Image Matching for Cross-Modal Remote Sensing Image Retrieval via Graph Neural Network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 812–824. 30 indexed citations
18.
Sun, Xian, Peijin Wang, Wanxuan Lu, et al.. (2022). RingMo: A Remote Sensing Foundation Model With Masked Image Modeling. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–22. 180 indexed citations breakdown →
19.
Lu, Wanxuan, Dong Gong, Kun Fu, et al.. (2021). Boundarymix: Generating pseudo-training images for improving segmentation with scribble annotations. Pattern Recognition. 117. 107924–107924. 7 indexed citations
20.
Fu, Kun, Wanxuan Lu, Wenhui Diao, et al.. (2018). WSF-NET: Weakly Supervised Feature-Fusion Network for Binary Segmentation in Remote Sensing Image. Remote Sensing. 10(12). 1970–1970. 56 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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