Pu Huang

715 total citations
29 papers, 445 citations indexed

About

Pu Huang is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Pu Huang has authored 29 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 12 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Artificial Intelligence. Recurrent topics in Pu Huang's work include AI in cancer detection (6 papers), Advanced Radiotherapy Techniques (5 papers) and Digital Imaging for Blood Diseases (4 papers). Pu Huang is often cited by papers focused on AI in cancer detection (6 papers), Advanced Radiotherapy Techniques (5 papers) and Digital Imaging for Blood Diseases (4 papers). Pu Huang collaborates with scholars based in China, United States and Australia. Pu Huang's co-authors include Dengwang Li, Cong Liu, Meirong Chen, Jie Li, Min Chen, Hui Zhu, Jianbo Wang, Yan Zhang, Zekun Jiang and Hua Zhang and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Medical Imaging and Pattern Recognition.

In The Last Decade

Pu Huang

27 papers receiving 437 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pu Huang China	13	192	163	133	55	52	29	445
Dzhoshkun I. Shakir United Kingdom	9	160 0.8×	221 1.4×	131 1.0×	105 1.9×	43 0.8×	22	532
Tri Huynh United States	7	161 0.8×	158 1.0×	147 1.1×	66 1.2×	46 0.9×	11	458
Liang Zeng China	6	132 0.7×	203 1.2×	116 0.9×	110 2.0×	77 1.5×	21	442
Yeqin Shao China	12	204 1.1×	204 1.3×	91 0.7×	163 3.0×	48 0.9×	38	458
Jiwoong Jeong United States	12	95 0.5×	244 1.5×	168 1.3×	127 2.3×	74 1.4×	34	609
Zhuo Zhao China	9	121 0.6×	78 0.5×	85 0.6×	50 0.9×	22 0.4×	37	387
Xinhua Cao United States	12	160 0.8×	225 1.4×	59 0.4×	55 1.0×	44 0.8×	46	575
Weihao Xie China	8	114 0.6×	112 0.7×	95 0.7×	49 0.9×	18 0.3×	24	400
Laurent Massoptier Italy	11	263 1.4×	252 1.5×	142 1.1×	128 2.3×	66 1.3×	23	543
Shanhui Sun United States	14	265 1.4×	361 2.2×	139 1.0×	140 2.5×	26 0.5×	31	677

Countries citing papers authored by Pu Huang

Since Specialization

Citations

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

Fields of papers citing papers by Pu Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pu Huang

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

Zhang⋆, Yin, et al.. (2025). Spacecraft component recognition based on frequency-spatial awareness and comparative auxiliary training strategy. Advances in Space Research. 77(1). 785–801.

Huang, Pu, Chang Su, Bowen Wu, & Zhangjing Yang. (2024). Global context aware dual channel pyramid model for robust image shadow removal. Engineering Applications of Artificial Intelligence. 133. 108552–108552.

Xue, Jie, et al.. (2024). QGFormer: Queries-guided transformer for flexible medical image synthesis with domain missing. Expert Systems with Applications. 247. 123318–123318. 5 indexed citations

Xue, Jie, Qi Li, Xiyu Liu, et al.. (2023). Hybrid neural-like P systems with evolutionary channels for multiple brain metastases segmentation. Pattern Recognition. 142. 109651–109651. 3 indexed citations

Liu, Xueyao, Xue–Yuan Dong, Tuo Li, et al.. (2023). A difficulty-aware and task-augmentation method based on meta-learning model for few-shot diabetic retinopathy classification. Quantitative Imaging in Medicine and Surgery. 14(1). 861–876. 2 indexed citations

Liu, Zhiming, et al.. (2022). RelationRS: Relationship Representation Network for Object Detection in Aerial Images. Remote Sensing. 14(8). 1862–1862. 4 indexed citations

Liu, Cong, Dengwang Li, & Pu Huang. (2021). ISE-YOLO: Improved Squeeze-and-Excitation Attention Module based YOLO for Blood Cells Detection. 2021 IEEE International Conference on Big Data (Big Data). 3911–3916. 23 indexed citations

Li, Dengwang, Hui Zhu, Min Chen, et al.. (2021). Generative adversarial networks in medical image segmentation: A review. Computers in Biology and Medicine. 140. 105063–105063. 106 indexed citations

Huang, Pu, et al.. (2020). Line of Sight and Image Motion Compensation for Step and Stare Imaging System. Applied Sciences. 10(20). 7119–7119. 9 indexed citations

10.

Ahmad, Sahar, Jiayu Huo, Pu Huang, et al.. (2020). SLIR: Synthesis, localization, inpainting, and registration for image-guided thermal ablation of liver tumors. Medical Image Analysis. 65. 101763–101763. 23 indexed citations

11.

Zhang, Yuan‐Ting, Zhiming Lu, Yajuan Shen, et al.. (2020). Hybrid adversarial‐discriminative network for leukocyte classification in leukemia. Medical Physics. 47(8). 3732–3744. 24 indexed citations

12.

Huang, Pu, Lin Su, Shuyang Chen, et al.. (2019). 2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning. Physics in Medicine and Biology. 64(18). 185006–185006. 21 indexed citations

13.

Huang, Pu, Gang Yu, Hua Lü, et al.. (2019). Attention‐aware fully convolutional neural network with convolutional long short‐term memory network for ultrasound‐based motion tracking. Medical Physics. 46(5). 2275–2285. 23 indexed citations

14.

Wang, Qianqian, et al.. (2019). A Hierarchical Attention Model for CTR Prediction Based on User Interest. IEEE Systems Journal. 14(3). 4015–4024. 18 indexed citations

15.

Huang, Pu, et al.. (2019). A Visual PCI Blockage Detection in Blast Furnace Raceway. ISIJ International. 60(3). 519–527. 13 indexed citations

16.

Huang, Pu, Changsheng Ma, Yupeng Zheng, et al.. (2018). Parotid gland radiation dose‐xerostomia relationships based on actual delivered dose for nasopharyngeal carcinoma. Journal of Applied Clinical Medical Physics. 19(3). 251–260. 20 indexed citations

17.

Huang, Pu, et al.. (2018). Multidimensional LSTM Networks to Predict Wind Speed. 7493–7497. 37 indexed citations

18.

Huang, Pu, Gang Yu, Daniel S. Kapp, et al.. (2017). Cumulative dose of radiation therapy of hepatocellular carcinoma patients and its deterministic relation to radiation-induced liver disease. Medical dosimetry. 43(3). 258–266. 5 indexed citations

19.

Huang, Pu, Gang Yu, Jinhu Chen, et al.. (2016). Investigation of dosimetric variations of liver radiotherapy using deformable registration of planning CT and cone‐beam CT. Journal of Applied Clinical Medical Physics. 18(1). 66–75. 5 indexed citations

20.

Li, Xuelan, et al.. (2008). Effect of behavior training on learning and memory of young rats with fetal growth restriction. Journal of Medical Colleges of PLA. 23(5). 283–288. 2 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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