Haigen Hu

1.7k total citations · 1 hit paper
61 papers, 1.1k citations indexed

About

Haigen Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Plant Science. According to data from OpenAlex, Haigen Hu has authored 61 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 16 papers in Plant Science. Recurrent topics in Haigen Hu's work include Greenhouse Technology and Climate Control (16 papers), Advanced Neural Network Applications (11 papers) and AI in cancer detection (9 papers). Haigen Hu is often cited by papers focused on Greenhouse Technology and Climate Control (16 papers), Advanced Neural Network Applications (11 papers) and AI in cancer detection (9 papers). Haigen Hu collaborates with scholars based in China, France and United States. Haigen Hu's co-authors include Qiu Guan, Lihong Xu, Qianwei Zhou, Yizhou Chen, Xu-Hua Yang, Huiling Chen, Zihan Wei, Ali Asghar Heidari, Ruihua Wei and Zhiwei Ji and has published in prestigious journals such as IEEE Access, Sensors and Pattern Recognition.

In The Last Decade

Haigen Hu

56 papers receiving 1.1k citations

Hit Papers

Generative Adversarial Networks in Medical Image augmenta... 2022 2026 2023 2024 2022 50 100 150 200 250
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. Generative Adversarial Networks in Medical Image augmentation: A review
    2022 251 citations Yizhou Chen, Xu-Hua Yang et al. Computers in Biology and Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haigen Hu China 18 342 283 237 234 84 61 1.1k
Michał Grochowski Poland 14 542 1.6× 486 1.7× 103 0.4× 342 1.5× 222 2.6× 36 1.7k
Agnieszka Mikołajczyk Poland 11 493 1.4× 497 1.8× 110 0.5× 249 1.1× 29 0.3× 19 1.6k
Akif Durdu Türkiye 20 358 1.0× 417 1.5× 167 0.7× 286 1.2× 248 3.0× 92 1.4k
Meng Zhao China 17 219 0.6× 274 1.0× 111 0.5× 80 0.3× 56 0.7× 97 955
Bo Zhao China 23 398 1.2× 956 3.4× 335 1.4× 172 0.7× 45 0.5× 93 1.9k
Jitendra V. Tembhurne India 13 402 1.2× 432 1.5× 121 0.5× 105 0.4× 26 0.3× 42 1.4k
Vatsala Anand India 18 454 1.3× 291 1.0× 235 1.0× 294 1.3× 22 0.3× 165 1.5k
Loretta Ichim Romania 15 239 0.7× 295 1.0× 157 0.7× 86 0.4× 64 0.8× 129 1.2k
Nizamettin Aydın Türkiye 24 386 1.1× 405 1.4× 434 1.8× 187 0.8× 157 1.9× 140 2.4k

Countries citing papers authored by Haigen Hu

Since Specialization
Citations

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

Fields of papers citing papers by Haigen Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haigen Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Haigen Hu. A scholar is included among the top collaborators of Haigen Hu 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 Haigen Hu. Haigen Hu 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.
Zhou, Qianwei, et al.. (2025). Multipath and noise resilient direction of arrival method for low-cost mechanical arm calibration. Computers & Electrical Engineering. 123. 110075–110075.
2.
Hu, Haigen, et al.. (2025). Auto-StyleMixer: A universal adaptive N-to-One framework for cross-domain data augmentation. Knowledge-Based Systems. 323. 113616–113616.
3.
Zhou, Qianwei, et al.. (2024). RMFDNet: Redundant and Missing Feature Decoupling Network for salient object detection. Engineering Applications of Artificial Intelligence. 139. 109459–109459.
4.
Hu, Haigen, et al.. (2024). HDConv: Heterogeneous kernel-based dilated convolutions. Neural Networks. 179. 106568–106568. 4 indexed citations
5.
Hu, Haigen, et al.. (2024). A comprehensive survey on contrastive learning. Neurocomputing. 610. 128645–128645. 41 indexed citations
6.
7.
8.
Chen, Yizhou, Xu-Hua Yang, Zihan Wei, et al.. (2022). Generative Adversarial Networks in Medical Image augmentation: A review. Computers in Biology and Medicine. 144. 105382–105382. 251 indexed citations breakdown →
9.
Zhou, Tongxue, Su Ruan, & Haigen Hu. (2022). A literature survey of MR-based brain tumor segmentation with missing modalities. Computerized Medical Imaging and Graphics. 104. 102167–102167. 25 indexed citations
10.
Jin, Zhichao, Haigen Hu, Qianwei Zhou, et al.. (2022). Joint Feature Learning for Cell Segmentation Based on Multi-scale Convolutional U-Net. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 1580–1585. 2 indexed citations
11.
Zhou, Qianwei, Baoqing Li, Tao Peng, et al.. (2022). Residual-recursive autoencoder for accelerated evolution in savonius wind turbines optimization. Neurocomputing. 500. 909–920. 2 indexed citations
12.
Pan, Jie, et al.. (2022). A Channel-Spatial Hybrid Attention Mechanism using Channel Weight Transfer Strategy. 2022 26th International Conference on Pattern Recognition (ICPR). 2524–2531. 1 indexed citations
13.
Hu, Haigen, et al.. (2021). An adaptive learning method of anchor shape priors for biological cells detection and segmentation. Computer Methods and Programs in Biomedicine. 208. 106260–106260. 11 indexed citations
14.
Yang, Rong, Yizhou Chen, Kangjie Li, et al.. (2021). CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network. Abdominal Radiology. 47(1). 232–241. 17 indexed citations
15.
Hu, Haigen, et al.. (2021). Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images. Pattern Recognition. 124. 108452–108452. 27 indexed citations
16.
Hu, Haigen, Pierre Decazes, Pierre Véra, Hua Li, & Su Ruan. (2019). Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy. International Journal of Computer Assisted Radiology and Surgery. 14(10). 1715–1724. 20 indexed citations
17.
Hu, Haigen, et al.. (2017). Detection and Recognition for Life State of Cell Cancer Using Two-Stage Cascade CNNs. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(3). 887–898. 28 indexed citations
18.
Chen, Jiaoliao, et al.. (2015). Modeling of Energy Demand in the Greenhouse Using PSO-GA Hybrid Algorithms. Mathematical Problems in Engineering. 2015. 1–6. 26 indexed citations
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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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