Pengxiang Wu

1.6k total citations · 1 hit paper
25 papers, 832 citations indexed

About

Pengxiang Wu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biophysics. According to data from OpenAlex, Pengxiang Wu has authored 25 papers receiving a total of 832 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 7 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Biophysics. Recurrent topics in Pengxiang Wu's work include Medical Image Segmentation Techniques (6 papers), Cell Image Analysis Techniques (6 papers) and Medical Imaging Techniques and Applications (5 papers). Pengxiang Wu is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Cell Image Analysis Techniques (6 papers) and Medical Imaging Techniques and Applications (5 papers). Pengxiang Wu collaborates with scholars based in United States, Netherlands and Sweden. Pengxiang Wu's co-authors include Dimitris Metaxas, Jingru Yi, Qiaoying Huang, Hui Qu, Siheng Chen, Bo Liu, Daniel J. Hoeppner, Dimitris Metaxas, Dong Yang and Menglin Jiang and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Medical Image Analysis and Laser & Photonics Review.

In The Last Decade

Pengxiang Wu

25 papers receiving 817 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.

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

2021 233 citations Jingru Yi, Pengxiang 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
Pengxiang Wu United States	14	516	193	160	150	121	25	832
Jingru Yi United States	12	398 0.8×	138 0.7×	158 1.0×	141 0.9×	90 0.7×	25	642
Elli Angelopoulou Germany	18	1.1k 2.1×	183 0.9×	305 1.9×	373 2.5×	105 0.9×	59	1.5k
Dmitry Nikolaev Russia	14	552 1.1×	125 0.6×	130 0.8×	120 0.8×	97 0.8×	164	893
Yao Sui China	16	551 1.1×	82 0.4×	53 0.3×	73 0.5×	173 1.4×	35	748
Nikolay Petkov Bulgaria	9	496 1.0×	126 0.7×	174 1.1×	76 0.5×	46 0.4×	55	895
Hae‐Gon Jeon South Korea	19	1.4k 2.8×	83 0.4×	514 3.2×	25 0.2×	144 1.2×	51	1.7k
F.C.A. Groen Netherlands	13	327 0.6×	80 0.4×	36 0.2×	54 0.4×	316 2.6×	64	809
Zhao Pei China	13	392 0.8×	95 0.5×	113 0.7×	25 0.2×	121 1.0×	60	634

Countries citing papers authored by Pengxiang Wu

Since Specialization

Citations

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

Fields of papers citing papers by Pengxiang Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengxiang Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Wang, Hanyu, Pengxiang Wu, Kevin Dela Rosa, Chen Wang, & Abhinav Shrivastava. (2024). Multimodality-guided Image Style Transfer using Cross-modal GAN Inversion. 4964–4973. 4 indexed citations

2.

Yi, Jingru, Pengxiang Wu, Bo Liu, et al.. (2021). Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors. 2149–2158. 233 indexed citations breakdown →

3.

Huang, Qiaoying, Yikun Xian, Dong Yang, et al.. (2020). Dynamic MRI reconstruction with end-to-end motion-guided network. Medical Image Analysis. 68. 101901–101901. 32 indexed citations

4.

Yi, Jingru, Hui Tang, Pengxiang Wu, et al.. (2020). Object-Guided Instance Segmentation for Biological Images. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 12677–12684. 10 indexed citations

5.

Kojima, Keisuke, Toshiaki Koike‐Akino, Ye Wang, et al.. (2020). Generative Deep Learning Model for a Multi-level Nano-Optic Broadband Power Splitter. Th1A.1–Th1A.1. 9 indexed citations

6.

Wu, Pengxiang, et al.. (2020). A Topological Filter for Learning with Label Noise. arXiv (Cornell University). 33. 21382–21393. 4 indexed citations

7.

Wu, Pengxiang, Hui Qu, Jingru Yi, et al.. (2019). Deep Attentive Feature Learning for Histopathology Image Classification. 1865–1868. 6 indexed citations

8.

Wu, Pengxiang, Chao Chen, Jingru Yi, & Dimitris Metaxas. (2019). Point Cloud Processing via Recurrent Set Encoding. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 5441–5449. 10 indexed citations

9.

Yi, Jingru, Pengxiang Wu, Qiaoying Huang, et al.. (2019). Online Neural Cell Tracking Using Blob-Seed Segmentation and Optical Flow. 3. 1057–1064. 2 indexed citations

10.

Zhang, Xudong, Pengxiang Wu, Changhe Yuan, et al.. (2019). Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction. 1312–1318. 3 indexed citations

11.

Yi, Jingru, Pengxiang Wu, & Dimitris Metaxas. (2019). ASSD: Attentive single shot multibox detector. Computer Vision and Image Understanding. 189. 102827–102827. 67 indexed citations

12.

Yi, Jingru, Pengxiang Wu, Menglin Jiang, et al.. (2019). Attentive neural cell instance segmentation. Medical Image Analysis. 55. 228–240. 66 indexed citations

13.

Huang, Qiaoying, Dong Yang, Pengxiang Wu, et al.. (2019). MRI Reconstruction Via Cascaded Channel-Wise Attention Network. 1622–1626. 46 indexed citations

14.

Qu, Hui, Gregory Riedlinger, Pengxiang Wu, et al.. (2019). Joint Segmentation and Fine-Grained Classification of Nuclei in Histopathology Images. 900–904. 27 indexed citations

15.

Yi, Jingru, Pengxiang Wu, Qiaoying Huang, et al.. (2019). Context-Refined Neural Cell Instance Segmentation. 1028–1032. 9 indexed citations

16.

Huang, Qiaoying, Dong Won Yang, Hui Qu, et al.. (2018). Dynamic MRI Reconstruction with Motion-Guided Network. 275–284. 2 indexed citations

17.

Yi, Jingru, Pengxiang Wu, Daniel J. Hoeppner, & Dimitris Metaxas. (2018). Pixel-wise neural cell instance segmentation. 373–377. 18 indexed citations

18.

Qu, Hui, Pengxiang Wu, Qiaoying Huang, et al.. (2018). Weakly Supervised Deep Nuclei Segmentation using Points Annotation in Histopathology Images. 390–400. 22 indexed citations

19.

Yang, Dong, et al.. (2017). 3D Motion Modeling and Reconstruction of Left Ventricle Wall in Cardiac MRI. Lecture notes in computer science. 10263. 481–492. 14 indexed citations

20.

Wu, Pengxiang, Jingru Yi, Gang Zhao, et al.. (2014). Active Contour-Based Cell Segmentation During Freezing and Its Application in Cryopreservation. IEEE Transactions on Biomedical Engineering. 62(1). 284–295. 23 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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