Fengbei Liu

813 total citations · 1 hit paper
10 papers, 333 citations indexed

About

Fengbei Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fengbei Liu has authored 10 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fengbei Liu's work include COVID-19 diagnosis using AI (3 papers), AI in cancer detection (2 papers) and Advanced Neural Network Applications (2 papers). Fengbei Liu is often cited by papers focused on COVID-19 diagnosis using AI (3 papers), AI in cancer detection (2 papers) and Advanced Neural Network Applications (2 papers). Fengbei Liu collaborates with scholars based in Australia, United Kingdom and United States. Fengbei Liu's co-authors include Gustavo Carneiro, Yuyuan Liu, Yuanhong Chen, Vasileios Belagiannis, Yu Tian, Helen Frazer, Chong Wang, Davis J. McCarthy, Guansong Pang and Yu Tian and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and IEEE Transactions on Medical Imaging.

In The Last Decade

Fengbei Liu

10 papers receiving 329 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.

Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

2022 180 citations Yuyuan Liu, Yu Tian et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fengbei Liu Australia	6	177	176	104	33	30	10	333
Zhiwei Cao China	8	211 1.2×	102 0.6×	145 1.4×	39 1.2×	30 1.0×	12	315
Ruihan Zhao China	5	217 1.2×	130 0.7×	131 1.3×	57 1.7×	22 0.7×	21	353
Jie-Neng Chen United States	3	263 1.5×	172 1.0×	90 0.9×	27 0.8×	22 0.7×	4	426
Chaoyu Chen China	8	146 0.8×	118 0.7×	98 0.9×	27 0.8×	14 0.5×	18	336
Yuanming Gao China	4	138 0.8×	109 0.6×	100 1.0×	53 1.6×	19 0.6×	9	276
Narinder Singh Punn India	6	153 0.9×	113 0.6×	130 1.3×	70 2.1×	16 0.5×	13	327
Matthew C. H. Lee United Kingdom	2	167 0.9×	109 0.6×	107 1.0×	19 0.6×	13 0.4×	2	288
Rushi Jiao China	4	167 0.9×	116 0.7×	116 1.1×	64 1.9×	16 0.5×	6	313
Jachih Fu Taiwan	10	154 0.9×	103 0.6×	96 0.9×	17 0.5×	46 1.5×	25	322
Weili Shi China	9	132 0.7×	66 0.4×	101 1.0×	32 1.0×	32 1.1×	64	297

Countries citing papers authored by Fengbei Liu

Since Specialization

Citations

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

Fields of papers citing papers by Fengbei Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengbei Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Fengbei Liu. A scholar is included among the top collaborators of Fengbei 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 Fengbei Liu. Fengbei Liu 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:

10 of 10 papers shown

1.

Wang, Chong, et al.. (2025). Cross- and Intra-Image Prototypical Learning for Multi-Label Disease Diagnosis and Interpretation. IEEE Transactions on Medical Imaging. 44(6). 2568–2580. 5 indexed citations

2.

Wang, Chong, Yuanhong Chen, Fengbei Liu, et al.. (2025). Mixture of Gaussian-Distributed Prototypes With Generative Modelling for Interpretable and Trustworthy Image Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(8). 6974–6989. 2 indexed citations

3.

Wang, Chong, Fengbei Liu, Michael S. Elliott, et al.. (2025). Progressive Mining and Dynamic Distillation of Hierarchical Prototypes for Disease Classification and Localisation. IEEE Journal of Biomedical and Health Informatics. 29(8). 5687–5699. 2 indexed citations

4.

Liu, Yuyuan, Wang Hu, Fengbei Liu, et al.. (2024). Unraveling Instance Associations: A Closer Look for Audio-Visual Segmentation. 26487–26497. 4 indexed citations

5.

Liu, Yuyuan, Chong Wang, Michael S. Elliott, et al.. (2024). BRAIxDet: Learning to detect malignant breast lesion with incomplete annotations. Medical Image Analysis. 96. 103192–103192. 5 indexed citations

6.

Tian, Yu, Fengbei Liu, Guansong Pang, et al.. (2023). Self-supervised pseudo multi-class pre-training for unsupervised anomaly detection and segmentation in medical images. Medical Image Analysis. 90. 102930–102930. 24 indexed citations

7.

Wang, Chong, Yuanhong Chen, Fengbei Liu, et al.. (2023). An Interpretable and Accurate Deep-Learning Diagnosis Framework Modeled With Fully and Semi-Supervised Reciprocal Learning. IEEE Transactions on Medical Imaging. 43(1). 392–404. 17 indexed citations

8.

Liu, Yuyuan, Yu Tian, Yuanhong Chen, et al.. (2022). Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4248–4257. 180 indexed citations breakdown →

9.

Liu, Fengbei, Yu Tian, Yuanhong Chen, et al.. (2022). ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 20665–20674. 76 indexed citations

10.

Takeda, Yu, Fengbei Liu, Fumio Sasazawa, et al.. (2020). Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning. IEEE Access. 8. 51853–51861. 18 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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