Bingzhi Chen

1.9k total citations · 2 hit papers
25 papers, 1.3k citations indexed

About

Bingzhi Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Bingzhi Chen has authored 25 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Bingzhi Chen's work include Emotion and Mood Recognition (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Medical Image Segmentation Techniques (4 papers). Bingzhi Chen is often cited by papers focused on Emotion and Mood Recognition (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Medical Image Segmentation Techniques (4 papers). Bingzhi Chen collaborates with scholars based in China, Singapore and United Kingdom. Bingzhi Chen's co-authors include Guangming Lu, Zheng Zhang, David Zhang, Jiayu Xu, Jinxing Li, Adams Wai‐Kin Kong, Yingjian Li, Yao Lu, Jiahui Pan and Zhihang Zhang and has published in prestigious journals such as IEEE Access, Neurocomputing and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Bingzhi Chen

20 papers receiving 1.2k citations

Hit Papers

DS-TransUNet: Dual Swin T... 2022 2026 2023 2024 2022 2023 200 400 600
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.

  1. DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation
    2022 601 citations Bingzhi Chen, Jiayu Xu et al. IEEE Transactions on Instrumentation and Measurement profile →
  2. TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation
    2023 188 citations Bingzhi Chen, Zheng Zhang et al. IEEE Transactions on Emerging Topics in Computational Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bingzhi Chen China 12 642 480 432 179 150 25 1.3k
Muhammad Arsalan South Korea 26 956 1.5× 353 0.7× 802 1.9× 113 0.6× 47 0.3× 76 1.9k
Bogdan J. Matuszewski United Kingdom 15 661 1.0× 486 1.0× 414 1.0× 75 0.4× 54 0.4× 74 1.3k
Junding Sun China 18 612 1.0× 462 1.0× 320 0.7× 358 2.0× 31 0.2× 90 1.5k
José Dolz Canada 23 826 1.3× 618 1.3× 720 1.7× 205 1.1× 26 0.2× 69 1.7k
Zhicheng Jiao United States 18 375 0.6× 518 1.1× 555 1.3× 167 0.9× 35 0.2× 73 1.3k
Malaya Kumar Nath India 21 493 0.8× 375 0.8× 534 1.2× 52 0.3× 59 0.4× 67 1.3k
Zhemin Zhuang China 18 297 0.5× 420 0.9× 391 0.9× 89 0.5× 31 0.2× 56 850
Emad Fatemizadeh Iran 18 498 0.8× 164 0.3× 308 0.7× 103 0.6× 103 0.7× 120 1.1k
Jonghye Woo United States 22 562 0.9× 418 0.9× 590 1.4× 51 0.3× 89 0.6× 117 1.5k
Veronika Cheplygina Netherlands 14 464 0.7× 593 1.2× 381 0.9× 60 0.3× 22 0.1× 24 1.3k

Countries citing papers authored by Bingzhi Chen

Since Specialization
Citations

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

Fields of papers citing papers by Bingzhi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bingzhi Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Bingzhi Chen. A scholar is included among the top collaborators of Bingzhi Chen 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 Bingzhi Chen. Bingzhi Chen 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.
Chen, Bingzhi, et al.. (2025). Towards Robust Semi-Supervised Distribution Alignment against Label Distribution Shift with Noisy Annotations. IEEE Transactions on Multimedia. 1–13. 1 indexed citations
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Chen, Bingzhi, et al.. (2024). Attention-Guided and Noise-Resistant Learning for Robust Medical Image Segmentation. IEEE Transactions on Instrumentation and Measurement. 73. 1–13. 5 indexed citations
4.
He, Lewei, et al.. (2024). A feature‐enhanced hybrid attention network for traffic sign recognition in real scenes. IET Image Processing. 18(8). 2064–2077. 1 indexed citations
5.
Zeng, Biqing, et al.. (2024). Context-aware graph embedding with gate and attention for session-based recommendation. Neurocomputing. 574. 127221–127221. 2 indexed citations
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Chen, Bingzhi, et al.. (2024). Stay Focused is All You Need for Adversarial Robustness. 6482–6491.
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Chen, Bingzhi, et al.. (2023). TransAttUnet: Multi-Level Attention-Guided U-Net With Transformer for Medical Image Segmentation. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(1). 55–68. 188 indexed citations breakdown →
12.
Chen, Bingzhi, et al.. (2022). DS-TransUNet: Dual Swin Transformer U-Net for Medical Image Segmentation. IEEE Transactions on Instrumentation and Measurement. 71. 1–15. 601 indexed citations breakdown →
13.
Li, Yingjian, Zheng Zhang, Bingzhi Chen, Guangming Lu, & David Zhang. (2022). Deep Margin-Sensitive Representation Learning for Cross-Domain Facial Expression Recognition. IEEE Transactions on Multimedia. 25. 1359–1373. 42 indexed citations
14.
Chen, Bingzhi, Zheng Zhang, Yingjian Li, Guangming Lu, & David Zhang. (2021). Multi-Label Chest X-Ray Image Classification via Semantic Similarity Graph Embedding. IEEE Transactions on Circuits and Systems for Video Technology. 32(4). 2455–2468. 48 indexed citations
15.
Chen, Bingzhi, Zheng Zhang, Yao Lu, et al.. (2021). Semantic-Interactive Graph Convolutional Network for Multilabel Image Recognition. IEEE Transactions on Systems Man and Cybernetics Systems. 52(8). 4887–4899. 22 indexed citations
16.
Chen, Bingzhi, et al.. (2021). Multimodal Emotion Recognition With Temporal and Semantic Consistency. IEEE/ACM Transactions on Audio Speech and Language Processing. 29. 3592–3603. 39 indexed citations
17.
Chen, Bingzhi, et al.. (2020). Label Co-Occurrence Learning With Graph Convolutional Networks for Multi-Label Chest X-Ray Image Classification. IEEE Journal of Biomedical and Health Informatics. 24(8). 2292–2302. 99 indexed citations
18.
Liu, Yishu, et al.. (2020). A New Technique for Diagnosis of Dental Caries on the Children’s First Permanent Molar. IEEE Access. 8. 185776–185785. 14 indexed citations
19.
Guo, Xiaobao, Jinxing Li, Bingzhi Chen, & Guangming Lu. (2019). Mask-Most Net: Mask Approximation Based Multi-oriented Scene Text Detection Network. 4. 206–211. 2 indexed citations
20.
Chen, Bingzhi, Jinxing Li, Guangming Lu, & David Zhang. (2019). Lesion Location Attention Guided Network for Multi-Label Thoracic Disease Classification in Chest X-Rays. IEEE Journal of Biomedical and Health Informatics. 24(7). 2016–2027. 63 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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