Bin Pu

1.0k total citations · 1 hit paper
50 papers, 638 citations indexed

About

Bin Pu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Bin Pu has authored 50 papers receiving a total of 638 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 11 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Bin Pu's work include Fetal and Pediatric Neurological Disorders (11 papers), Domain Adaptation and Few-Shot Learning (9 papers) and AI in cancer detection (7 papers). Bin Pu is often cited by papers focused on Fetal and Pediatric Neurological Disorders (11 papers), Domain Adaptation and Few-Shot Learning (9 papers) and AI in cancer detection (7 papers). Bin Pu collaborates with scholars based in China, Hong Kong and United Kingdom. Bin Pu's co-authors include Kenli Li, Ningbo Zhu, Shengli Li, Jianguo Chen, Yan Kang, Philip S. Yu, Wanli Xie, Wei Wei, Xiangke Liao and Xinping Guan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Bin Pu

39 papers receiving 622 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.

Automatic Fetal Ultrasound Standard Plane Recognition Based on Deep Learning and IIoT

2021 157 citations Bin Pu, Kenli Li et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bin Pu China	13	271	138	112	78	69	50	638
Ningbo Zhu China	17	397 1.5×	358 2.6×	78 0.7×	60 0.8×	139 2.0×	49	958
M. Anwar Ma’sum Indonesia	13	145 0.5×	202 1.5×	47 0.4×	64 0.8×	21 0.3×	59	599
Puspanjali Mohapatra India	12	385 1.4×	127 0.9×	34 0.3×	53 0.7×	61 0.9×	39	663
Xiaoming You China	14	281 1.0×	160 1.2×	44 0.4×	51 0.7×	5 0.1×	70	761
Amir Nakib France	16	224 0.8×	262 1.9×	8 0.1×	72 0.9×	50 0.7×	82	1.1k
Jafar Tanha Iran	13	512 1.9×	178 1.3×	8 0.1×	59 0.8×	40 0.6×	76	841
Maha Sharkas Egypt	17	636 2.3×	318 2.3×	59 0.5×	130 1.7×	523 7.6×	40	1.1k
Yuguang Yan China	16	506 1.9×	290 2.1×	15 0.1×	36 0.5×	37 0.5×	38	718
N. Sri Madhava Raja India	16	464 1.7×	488 3.5×	24 0.2×	36 0.5×	543 7.9×	46	1.3k
Ishfaq Yaseen Saudi Arabia	14	254 0.9×	92 0.7×	6 0.1×	50 0.6×	93 1.3×	95	629

Countries citing papers authored by Bin Pu

Since Specialization

Citations

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

Fields of papers citing papers by Bin Pu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bin Pu

This figure shows the co-authorship network connecting the top 25 collaborators of Bin Pu. A scholar is included among the top collaborators of Bin Pu 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 Bin Pu. Bin Pu 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.

Yu, Xiang, Yue Qin, Yimei Liao, et al.. (2025). Simple is what you need for efficient and accurate medical image segmentation. Expert Systems with Applications. 304. 130687–130687.

2.

Pu, Bin, et al.. (2025). TS-RePSO: A Three-Stage Feature Selection Method Combing ReliefF and PSO in Bioinformatics. PubMed. 22(2). 640–652. 2 indexed citations

3.

Sun, Junding, et al.. (2025). SAGCN: Self-adaptive Graph Convolutional Network for pneumonia detection. Biomedical Signal Processing and Control. 106. 107634–107634. 1 indexed citations

4.

Dong, Xingbo, et al.. (2025). Low-light image enhancement with luminance duality. Knowledge-Based Systems. 329. 114420–114420.

5.

Dong, Xingbo, et al.. (2025). CertainTTA: Estimating uncertainty for test-time adaptation on medical image segmentation. Information Fusion. 123. 103300–103300.

6.

Zhu, Ningbo, et al.. (2024). ThyFusion: A lightweight attribute enhancement module for thyroid nodule diagnosis using gradient and frequency-domain awareness. Neurocomputing. 613. 128749–128749. 2 indexed citations

7.

Pu, Bin, et al.. (2024). DGGI: Deep Generative Gradient Inversion with diffusion model. Information Fusion. 113. 102620–102620. 2 indexed citations

8.

Tan, Guanghua, et al.. (2024). Graph-enhanced ensembles of multi-scale structure perception deep architecture for fetal ultrasound plane recognition. Engineering Applications of Artificial Intelligence. 136. 108885–108885. 2 indexed citations

9.

Zhao, Lei, et al.. (2024). Boosting the Transferability of Ensemble Adversarial Attack via Stochastic Average Variance Descent. IET Information Security. 2024(1).

10.

Kang, Yan, et al.. (2024). HICL: Hierarchical Intent Contrastive Learning for sequential recommendation. Expert Systems with Applications. 251. 123886–123886. 4 indexed citations

11.

Pu, Bin, et al.. (2024). HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos. IEEE Journal of Biomedical and Health Informatics. 28(5). 2943–2954. 11 indexed citations

12.

Zhao, Lei, et al.. (2024). A multi-label image classification method combining multi-stage image semantic information and label relevance. International Journal of Machine Learning and Cybernetics. 15(9). 3911–3925. 1 indexed citations

13.

Liang, Bin, et al.. (2024). TKR-FSOD: Fetal Anatomical Structure Few-Shot Detection Utilizing Topological Knowledge Reasoning. IEEE Journal of Biomedical and Health Informatics. 29(1). 547–557.

14.

Chen, Zhuangzhuang, et al.. (2024). Divide and augment: Supervised domain adaptation via sample-wise feature fusion. Information Fusion. 115. 102757–102757. 5 indexed citations

15.

Pan, Feng, et al.. (2023). An end-to-end anti-shaking multi-focus image fusion approach. Image and Vision Computing. 137. 104788–104788. 5 indexed citations

16.

Kang, Yan, et al.. (2023). TMHSCA: a novel hybrid two-stage mutation with a sine cosine algorithm for discounted {0-1} knapsack problems. Neural Computing and Applications. 35(17). 12691–12713. 4 indexed citations

17.

Pu, Bin, et al.. (2023). Siamese refine polar mask prediction network for visual tracking. Signal Image and Video Processing. 18(1). 923–933.

18.

Tian, Zean, et al.. (2023). Deep endpoints focusing network under geometric constraints for end-to-end biometric measurement in fetal ultrasound images. Computers in Biology and Medicine. 165. 107399–107399. 6 indexed citations

19.

Tan, Guanghua, et al.. (2023). A knowledge-interpretable multi-task learning framework for automated thyroid nodule diagnosis in ultrasound videos. Medical Image Analysis. 91. 103039–103039. 10 indexed citations

20.

Kang, Yan, Bin Pu, Yun Yang, et al.. (2022). A Deep Graph Network with Multiple Similarity for User Clustering in Human–Computer Interaction. ACM Transactions on Multimedia Computing Communications and Applications. 20(2). 1–20. 5 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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