Weiquan Liu

836 total citations
52 papers, 501 citations indexed

About

Weiquan Liu is a scholar working on Computer Vision and Pattern Recognition, Geology and Environmental Engineering. According to data from OpenAlex, Weiquan Liu has authored 52 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 19 papers in Geology and 16 papers in Environmental Engineering. Recurrent topics in Weiquan Liu's work include 3D Surveying and Cultural Heritage (19 papers), Remote Sensing and LiDAR Applications (14 papers) and 3D Shape Modeling and Analysis (12 papers). Weiquan Liu is often cited by papers focused on 3D Surveying and Cultural Heritage (19 papers), Remote Sensing and LiDAR Applications (14 papers) and 3D Shape Modeling and Analysis (12 papers). Weiquan Liu collaborates with scholars based in China, Canada and Taiwan. Weiquan Liu's co-authors include Cheng Wang, Xuesheng Bian, Jonathan Li, Yu Zang, Ming Cheng, Yanfei Su, Zhimin Yuan, Chenglu Wen, Zhihong Zhang and Xióngbiāo Luó and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, The British Journal of Psychiatry and Pattern Recognition.

In The Last Decade

Weiquan Liu

45 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weiquan Liu China 13 169 159 130 97 84 52 501
Yan Xia China 15 322 1.9× 100 0.6× 70 0.5× 103 1.1× 74 0.9× 52 661
Amal Rannen Triki Belgium 3 332 2.0× 44 0.3× 106 0.8× 64 0.7× 110 1.3× 4 602
Hossam Isack Canada 6 581 3.4× 152 1.0× 166 1.3× 79 0.8× 127 1.5× 10 814
Qiulei Dong China 14 302 1.8× 199 1.3× 195 1.5× 199 2.1× 105 1.3× 68 662
Yunyang Xiong United States 8 249 1.5× 38 0.2× 32 0.2× 48 0.5× 128 1.5× 16 479
Guofeng Tong China 12 176 1.0× 76 0.5× 80 0.6× 60 0.6× 74 0.9× 45 458
Felipe Lumbreras Spain 14 611 3.6× 50 0.3× 89 0.7× 34 0.4× 56 0.7× 50 852
Yansong Duan China 13 495 2.9× 107 0.7× 104 0.8× 86 0.9× 82 1.0× 50 932
Xun Xu Singapore 12 253 1.5× 142 0.9× 123 0.9× 166 1.7× 100 1.2× 28 506
Lijun Ding China 5 273 1.6× 24 0.2× 30 0.2× 35 0.4× 62 0.7× 9 526

Countries citing papers authored by Weiquan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Weiquan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiquan Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Weiquan Liu. A scholar is included among the top collaborators of Weiquan Liu 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 Weiquan Liu. Weiquan Liu 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.
Bian, Xuesheng, Shuting Chen, & Weiquan Liu. (2025). Ins-ATP: Deep estimation of ATP for organoid based on high throughput microscope images. Methods. 235. 34–44.
2.
3.
Bian, Xuesheng, et al.. (2025). ThreeF-Net: Fine-grained feature fusion network for breast ultrasound image segmentation. Computers in Biology and Medicine. 194. 110527–110527.
4.
Liu, Jia, Jun Shao, Sen Xu, et al.. (2024). Asym-UNet: An asymmetric U-shape Network for breast lesions ultrasound images segmentation. Biomedical Signal Processing and Control. 99. 106822–106822. 6 indexed citations
5.
Liu, Weiquan, et al.. (2024). Robust multi-model fitting via neighborhood graph structure consistency. Digital Signal Processing. 147. 104402–104402. 1 indexed citations
6.
Cheng, Ming, Zhimin Yuan, Wei Dai, et al.. (2024). Domain adaptive remote sensing image semantic segmentation with prototype guidance. Neurocomputing. 580. 127484–127484. 4 indexed citations
7.
Zheng, Shijun, Weiquan Liu, Yu Zang, et al.. (2024). SR-Adv: Salient Region Adversarial Attacks on 3D Point Clouds for Autonomous Driving. IEEE Transactions on Intelligent Transportation Systems. 25(10). 14019–14030. 4 indexed citations
8.
Yuan, Zhimin, Ming Cheng, Yanfei Su, et al.. (2023). Prototype-Guided Multitask Adversarial Network for Cross-Domain LiDAR Point Clouds Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–13. 14 indexed citations
9.
Zang, Yu, et al.. (2023). LCE-NET: Contour Extraction for Large-Scale 3-D Point Clouds. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–13. 7 indexed citations
10.
Wang, Zhiyong, et al.. (2023). DSMNet: Deep High-Precision 3-D Surface Modeling From Sparse Point Cloud Frames. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 6 indexed citations
11.
Su, Yanfei, et al.. (2023). Multistage Scene-Level Constraints for Large-Scale Point Cloud Weakly Supervised Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–18. 7 indexed citations
12.
Yuan, Zhimin, Chenglu Wen, Ming Cheng, et al.. (2022). Category-Level Adversaries for Outdoor LiDAR Point Clouds Cross-Domain Semantic Segmentation. IEEE Transactions on Intelligent Transportation Systems. 1–12. 18 indexed citations
13.
Liu, Weiquan, Yu Zang, Lei Zhao, et al.. (2022). Intracity Temperature Estimation by Physics Informed Neural Network Using Modeled Forcing Meteorology and Multispectral Satellite Imagery. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–15. 3 indexed citations
14.
Su, Yanfei, Weiquan Liu, Ming Cheng, Zhimin Yuan, & Cheng Wang. (2021). Local Fusion Attention Network for Semantic Segmentation of Building Facade Point Clouds. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 5 indexed citations
15.
Bian, Xuesheng, et al.. (2021). A deep learning model for detection and tracking in high-throughput images of organoid. Computers in Biology and Medicine. 134. 104490–104490. 52 indexed citations
16.
Liu, Weiquan, Cheng Wang, Guorong Cai, et al.. (2020). Ground Camera Image and Large-Scale 3-D Image-Based Point Cloud Registration Based on Learning Domain Invariant Feature Descriptors. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 997–1009. 5 indexed citations
17.
Liu, Weiquan, Cheng Wang, Xuesheng Bian, et al.. (2019). AE-GAN-Net: Learning Invariant Feature Descriptor to Match Ground Camera Images and a Large-Scale 3D Image-Based Point Cloud for Outdoor Augmented Reality. Remote Sensing. 11(19). 2243–2243. 7 indexed citations
18.
Xia, Yan, Cheng Wang, Yusheng Xu, et al.. (2019). RealPoint3D: Generating 3D Point Clouds from a Single Image of Complex Scenarios. Remote Sensing. 11(22). 2644–2644. 11 indexed citations
19.
Liu, Weiquan, Cheng Wang, Xuesheng Bian, et al.. (2019). Learning to Match Ground Camera Image and UAV 3-D Model-Rendered Image Based on Siamese Network With Attention Mechanism. IEEE Geoscience and Remote Sensing Letters. 17(9). 1608–1612. 3 indexed citations
20.
Li, Wei, Cheng Wang, Dawei Zai, et al.. (2018). A Volumetric Fusing Method for TLS and SFM Point Clouds. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(9). 3349–3357. 9 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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