Lifan Zhou

883 total citations
47 papers, 641 citations indexed

About

Lifan Zhou is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Environmental Engineering. According to data from OpenAlex, Lifan Zhou has authored 47 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Aerospace Engineering, 15 papers in Computer Vision and Pattern Recognition and 12 papers in Environmental Engineering. Recurrent topics in Lifan Zhou's work include Synthetic Aperture Radar (SAR) Applications and Techniques (27 papers), Advanced SAR Imaging Techniques (18 papers) and Soil Moisture and Remote Sensing (10 papers). Lifan Zhou is often cited by papers focused on Synthetic Aperture Radar (SAR) Applications and Techniques (27 papers), Advanced SAR Imaging Techniques (18 papers) and Soil Moisture and Remote Sensing (10 papers). Lifan Zhou collaborates with scholars based in China, United States and Hong Kong. Lifan Zhou's co-authors include Hanwen Yu, Yang Lan, Mengdao Xing, Shengrong Gong, Vito Pascazio, Shan Zhong, Dengrong Zhang, Yong Wang, Delu Pan and Peifeng Ma and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Sensors.

In The Last Decade

Lifan Zhou

42 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lifan Zhou China 12 416 240 121 98 94 47 641
Marc Jäger Germany 15 769 1.8× 252 1.1× 238 2.0× 157 1.6× 114 1.2× 61 1.2k
Zhen Ye China 14 222 0.5× 323 1.3× 171 1.4× 56 0.6× 91 1.0× 50 682
Catherine Proy France 7 186 0.4× 297 1.2× 142 1.2× 165 1.7× 40 0.4× 16 766
Filippo Biondi Italy 16 443 1.1× 58 0.2× 66 0.5× 46 0.5× 102 1.1× 40 618
Ryo Natsuaki Japan 13 382 0.9× 37 0.2× 139 1.1× 141 1.4× 64 0.7× 109 772
Zhihua Xu China 16 176 0.4× 177 0.7× 195 1.6× 21 0.2× 74 0.8× 65 734
Paolo Dabove Italy 16 533 1.3× 60 0.3× 191 1.6× 32 0.3× 89 0.9× 76 912
Nan Ge China 10 176 0.4× 103 0.4× 100 0.8× 163 1.7× 42 0.4× 27 520
Claudio Maria Prati Italy 16 905 2.2× 103 0.4× 216 1.8× 192 2.0× 161 1.7× 44 1.1k
Ulrich Thoennessen Germany 12 618 1.5× 503 2.1× 325 2.7× 99 1.0× 234 2.5× 50 1.1k

Countries citing papers authored by Lifan Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Lifan Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lifan Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Lifan Zhou. A scholar is included among the top collaborators of Lifan Zhou 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 Lifan Zhou. Lifan Zhou 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.
Zhou, Lifan & Hanwen Yu. (2025). MoDL-PU: Model-Based Deep Learning for InSAR Phase Unwrapping. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–11. 2 indexed citations
2.
Zhou, Lifan, et al.. (2025). Transformer-Based Semantic Segmentation for Flood Region Recognition in SAR Images. 6(3). 222–229. 3 indexed citations
3.
Zhou, Xuanyu, et al.. (2024). Local–Global Multiscale Fusion Network for Semantic Segmentation of Buildings in SAR Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 7410–7421. 3 indexed citations
4.
Liu, Wei, Lifan Zhou, Shan Zhong, & Shengrong Gong. (2024). Semantic Assistance in SAR Object Detection: A Mask-Guided Approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 19395–19407. 2 indexed citations
5.
Liu, Wei & Lifan Zhou. (2024). Multilevel Denoising for High-Quality SAR Object Detection in Complex Scenes. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–13. 3 indexed citations
6.
Zhou, Lifan & Hanwen Yu. (2024). InSAR-DLPU: A benchmark dataset for deep learning-based synthetic aperture radar interferometry phase unwrapping [Software and Data Sets]. IEEE Geoscience and Remote Sensing Magazine. 12(2). 118–124. 2 indexed citations
7.
Zhou, Lifan, et al.. (2024). Multi-temporal InSAR evidence of non-tidal ocean loading effects from Chaoshan coastal plain, China. International Journal of Applied Earth Observation and Geoinformation. 132. 104031–104031.
8.
9.
Zhou, Lifan & Hanwen Yu. (2023). A Novel Mathematical Framework for Multibaseline InSAR Phase Unwrapping. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–8. 10 indexed citations
10.
Zhou, Xuanyu, et al.. (2023). Swin Transformer Embedding Dual-Stream for Semantic Segmentation of Remote Sensing Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 175–189. 22 indexed citations
11.
Zhou, Xuanyu, Lifan Zhou, Shengrong Gong, et al.. (2023). Hybrid CNN and Transformer Network for Semantic Segmentation of UAV Remote Sensing Images. 5(1). 33–41. 4 indexed citations
12.
Zhou, Lifan, Hanwen Yu, Vito Pascazio, & Mengdao Xing. (2022). PU-GAN: A One-Step 2-D InSAR Phase Unwrapping Based on Conditional Generative Adversarial Network. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–10. 58 indexed citations
13.
Zhong, Shan, et al.. (2022). Visual Tracking With Reinforced Template Updating and Redetection Discriminator. 4(1). 70–75. 1 indexed citations
14.
Yu, Hanwen, et al.. (2022). PDNet: A Lightweight Deep Convolutional Neural Network for InSAR Phase Denoising. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–9. 28 indexed citations
15.
Zhou, Lifan, Hanwen Yu, Yang Lan, Shengrong Gong, & Mengdao Xing. (2021). CANet: An Unsupervised Deep Convolutional Neural Network for Efficient Cluster-Analysis-Based Multibaseline InSAR Phase Unwrapping. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–15. 42 indexed citations
16.
Zhou, Lifan, Hanwen Yu, Yang Lan, & Mengdao Xing. (2021). Deep Learning-Based Branch-Cut Method for InSAR Two-Dimensional Phase Unwrapping. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–15. 70 indexed citations
17.
Zhou, Lifan, Hanwen Yu, Yang Lan, & Mengdao Xing. (2021). Artificial Intelligence In Interferometric Synthetic Aperture Radar Phase Unwrapping: A Review. IEEE Geoscience and Remote Sensing Magazine. 9(2). 10–28. 67 indexed citations
18.
Zhou, Lifan, Hanwen Yu, & Yang Lan. (2020). Deep Convolutional Neural Network-Based Robust Phase Gradient Estimation for Two-Dimensional Phase Unwrapping Using SAR Interferograms. IEEE Transactions on Geoscience and Remote Sensing. 58(7). 4653–4665. 99 indexed citations
19.
20.
Ji, Guang, Zhaohui Wang, Lifan Zhou, et al.. (2020). SAR Image Colorization Using Multidomain Cycle-Consistency Generative Adversarial Network. IEEE Geoscience and Remote Sensing Letters. 18(2). 296–300. 37 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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