Keyan Wang

1.6k total citations · 1 hit paper
59 papers, 1.0k citations indexed

About

Keyan Wang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Electrical and Electronic Engineering. According to data from OpenAlex, Keyan Wang has authored 59 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computer Vision and Pattern Recognition, 16 papers in Media Technology and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Keyan Wang's work include Image Enhancement Techniques (13 papers), Advanced Image Fusion Techniques (11 papers) and Advanced Data Compression Techniques (11 papers). Keyan Wang is often cited by papers focused on Image Enhancement Techniques (13 papers), Advanced Image Fusion Techniques (11 papers) and Advanced Data Compression Techniques (11 papers). Keyan Wang collaborates with scholars based in China, Canada and United States. Keyan Wang's co-authors include Yunsong Li, Jun Chen, Huan Liu, Jiaojiao Li, Qian Du, Minghan Fu, Shirui Huang, Xi Zhao, Muhammad Alrabeiah and Bobo Xi and has published in prestigious journals such as IEEE Access, Organic Letters and Anesthesia & Analgesia.

In The Last Decade

Keyan Wang

53 papers receiving 1000 citations

Hit Papers

Contrastive Semi-Supervised Learning for Underwater Image... 2023 2026 2024 2025 2023 40 80 120
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. Contrastive Semi-Supervised Learning for Underwater Image Restoration via Reliable Bank
    2023 139 citations Shirui Huang, Keyan Wang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Keyan Wang China 17 648 472 109 67 67 59 1.0k
Yazhou Liu China 17 369 0.6× 106 0.2× 55 0.5× 20 0.3× 28 0.4× 47 775
Zhihang Li China 12 523 0.8× 80 0.2× 15 0.1× 41 0.6× 71 1.1× 32 891
Junwei Wang China 15 264 0.4× 155 0.3× 77 0.7× 83 1.2× 113 1.7× 67 865
Bin Luo China 14 389 0.6× 149 0.3× 34 0.3× 4 0.1× 69 1.0× 45 711
Lin He China 13 185 0.3× 55 0.1× 101 0.9× 18 0.3× 12 0.2× 62 733
Chunhui Zhao China 19 351 0.5× 930 2.0× 451 4.1× 10 0.1× 142 2.1× 92 1.2k
T. Chang United States 5 797 1.2× 325 0.7× 45 0.4× 4 0.1× 27 0.4× 8 1.0k

Countries citing papers authored by Keyan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Keyan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keyan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Keyan Wang. A scholar is included among the top collaborators of Keyan Wang 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 Keyan Wang. Keyan Wang 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
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Wang, Keyan, Jiansong Ji, Scott M. Bugenhagen, et al.. (2025). Altered Myocardial Oxygenation and Impaired Energy Efficiency: A Pilot Study in Patients With Light Chain Cardiac Amyloidosis. Journal of Magnetic Resonance Imaging. 63(3). 848–856.
3.
Wang, Keyan, Jicheng Sun, Xiaoyu Zhang, et al.. (2025). Advances and Challenges in Nano-Delivery Systems for Glioblastoma Treatment: A Comprehensive Review. International Journal of Nanomedicine. Volume 20. 9597–9620. 1 indexed citations
4.
Wang, Keyan, et al.. (2024). AFE-Net: Attention-Guided Feature Enhancement Network for Infrared Small Target Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 4208–4221. 16 indexed citations
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Wang, Keyan, et al.. (2023). MashFormer: A Novel Multiscale Aware Hybrid Detector for Remote Sensing Object Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 2753–2763. 21 indexed citations
8.
Wang, Keyan, Shirui Huang, & Yunsong Li. (2022). An optical reconstruction based underwater image analysis. Journal of Image and Graphics. 27(5). 1337–1358. 1 indexed citations
9.
Ge, Chiru, Qian Du, Weiwei Sun, et al.. (2021). Deep Residual Network-Based Fusion Framework for Hyperspectral and LiDAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 2458–2472. 34 indexed citations
10.
Wang, Keyan, et al.. (2020). Accelerating Haze Removal Algorithm Using CUDA. Remote Sensing. 13(1). 85–85. 6 indexed citations
11.
Xie, Weiying, et al.. (2020). Background Learning Based on Target Suppression Constraint for Hyperspectral Target Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 5887–5897. 73 indexed citations
12.
Zheng, Yuxuan, et al.. (2019). Deep Residual Learning for Boosting the Accuracy of Hyperspectral Pansharpening. IEEE Geoscience and Remote Sensing Letters. 17(8). 1435–1439. 36 indexed citations
13.
Wang, Keyan, et al.. (2019). Underwater Image Restoration Based on a Parallel Convolutional Neural Network. Remote Sensing. 11(13). 1591–1591. 53 indexed citations
14.
Alrabeiah, Muhammad, et al.. (2019). Single Image Dehazing with a Generic Model-Agnostic Convolutional Neural Network. IEEE Signal Processing Letters. 26(6). 833–837. 94 indexed citations
15.
Hu, Yan, Keyan Wang, Xi Zhao, Hui Wang, & Yunsong Li. (2018). Underwater Image Restoration Based on Convolutional Neural Network. Asian Conference on Machine Learning. 296–311. 20 indexed citations
16.
Wang, Keyan, Hui Wang, Yufei Li, Yan Hu, & Yunsong Li. (2018). Quantitative Performance Evaluation for Dehazing Algorithms on Synthetic Outdoor Hazy Images. IEEE Access. 6. 20481–20496. 6 indexed citations
17.
Li, Yufei, Keyan Wang, Ning Xu, & Yunsong Li. (2017). Quantitative evaluation for dehazing algorithms on synthetic outdoor hazy dataset. 1–4. 2 indexed citations
18.
Guo, Jie, Yunsong Li, Kai Liu, Jie Lei, & Keyan Wang. (2017). Fast FPGA Implementation for Computing the Pixel Purity Index of Hyperspectral Images. Journal of Circuits Systems and Computers. 27(3). 1850045–1850045. 5 indexed citations
19.
Wang, Keyan. (2011). Lossless and Near-Lossless Compression of Hyperspectral Images Based on Search for L_∞ Minimum and Coset Coding. Dianzi xuebao. 3 indexed citations
20.
Li, Yunsong, et al.. (2008). Efficient rate control algorithm for JPEG2000 based on PSMSD. Systems engineering and electronics. 30(1). 176–180. 1 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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