Chenyu Li

2.4k total citations · 6 hit papers
28 papers, 1.6k citations indexed

About

Chenyu Li is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Ocean Engineering. According to data from OpenAlex, Chenyu Li has authored 28 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Media Technology, 11 papers in Computer Vision and Pattern Recognition and 4 papers in Ocean Engineering. Recurrent topics in Chenyu Li's work include Remote-Sensing Image Classification (13 papers), Advanced Image Fusion Techniques (8 papers) and Image and Signal Denoising Methods (4 papers). Chenyu Li is often cited by papers focused on Remote-Sensing Image Classification (13 papers), Advanced Image Fusion Techniques (8 papers) and Image and Signal Denoising Methods (4 papers). Chenyu Li collaborates with scholars based in China, France and Japan. Chenyu Li's co-authors include Danfeng Hong, Jocelyn Chanussot, Jing Yao, Bing Zhang, Naoto Yokoya, Antonio Plaza, Jón Atli Benediktsson, Yuxuan Li, Xiuping Jia and Qing Dai and has published in prestigious journals such as Advanced Materials, Journal of Applied Physics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Chenyu Li

23 papers receiving 1.6k citations

Hit Papers

SpectralGPT: Spectral Remote Sensing Foundation Model 2023 2026 2024 2025 2024 2023 2023 2023 2024 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chenyu Li China 14 832 516 302 228 169 28 1.6k
Jiaxin Li China 17 862 1.0× 523 1.0× 185 0.6× 157 0.7× 195 1.2× 84 1.7k
Konstantinos Makantasis Greece 15 686 0.8× 425 0.8× 436 1.4× 171 0.8× 91 0.5× 50 1.4k
Cheng Shi China 23 846 1.0× 646 1.3× 353 1.2× 187 0.8× 80 0.5× 100 1.8k
Hongmin Gao China 27 1.2k 1.4× 576 1.1× 598 2.0× 265 1.2× 239 1.4× 173 2.0k
Xiaofei Yang China 18 794 1.0× 410 0.8× 402 1.3× 216 0.9× 92 0.5× 98 1.8k
Junping Zhang China 20 1.2k 1.4× 632 1.2× 546 1.8× 171 0.8× 213 1.3× 167 1.7k
Feng Zhou China 23 704 0.8× 494 1.0× 377 1.2× 123 0.5× 139 0.8× 79 1.9k
Ning Zhang China 22 531 0.6× 793 1.5× 205 0.7× 250 1.1× 168 1.0× 109 1.7k
Zhu Han China 13 1.2k 1.4× 423 0.8× 598 2.0× 182 0.8× 177 1.0× 43 1.6k

Countries citing papers authored by Chenyu Li

Since Specialization
Citations

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

Fields of papers citing papers by Chenyu Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chenyu Li

This figure shows the co-authorship network connecting the top 25 collaborators of Chenyu Li. A scholar is included among the top collaborators of Chenyu Li 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 Chenyu Li. Chenyu Li 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.
Ding, Lei, Danfeng Hong, Hongruixuan Chen, et al.. (2025). A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, strategies, and challenges. IEEE Geoscience and Remote Sensing Magazine. 13(3). 164–189. 7 indexed citations
2.
Ahmad, Muhammad, Salvatore Distefano, Adil Khan, et al.. (2025). A comprehensive survey for Hyperspectral Image Classification: The evolution from conventional to transformers and Mamba models. Neurocomputing. 644. 130428–130428. 9 indexed citations
3.
Li, Xuyang, Chenyu Li, Gemine Vivone, & Danfeng Hong. (2025). SeaMo: A season-aware multimodal foundation model for remote sensing. Information Fusion. 125. 103334–103334. 1 indexed citations
5.
Pan, Zhenkuan, et al.. (2024). HyperSINet: A Synergetic Interaction Network Combined With Convolution and Transformer for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–18. 16 indexed citations
6.
Li, Chenyu, Bing Zhang, Danfeng Hong, et al.. (2024). Interpretable Networks for Hyperspectral Anomaly Detection: A Deep Unfolding Solution. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 6 indexed citations
7.
Hong, Danfeng, Bing Zhang, Xuyang Li, et al.. (2024). SpectralGPT: Spectral Remote Sensing Foundation Model. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(8). 5227–5244. 467 indexed citations breakdown →
8.
Vivone, Gemine, Liang-Jian Deng, Danfeng Hong, et al.. (2024). Deep Learning in Remote Sensing Image Fusion: Methods, protocols, data, and future perspectives. IEEE Geoscience and Remote Sensing Magazine. 13(1). 269–310. 23 indexed citations
9.
Li, Chenyu, Danfeng Hong, & Bing Zhang. (2024). Deep unfolding network for hyperspectral anomaly detection. National Remote Sensing Bulletin. 28(1). 69–77.
10.
Hong, Danfeng, Chenyu Li, Bing Zhang, et al.. (2024). Multimodal artificial intelligence foundation models: Unleashing the power of remote sensing big data in earth observation. Opin vísindi (Opin vísindi). 2(1). 100055–100055. 65 indexed citations breakdown →
11.
Li, Chenyu, et al.. (2024). Hyperspectral Image Classification With Mamba. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14. 24 indexed citations
12.
Li, Chenyu, et al.. (2024). Research on the mechanism of organizing and managing mainstream integrated media information resources in the era of big data. Expert Systems with Applications. 266. 126128–126128.
13.
Li, Chenyu, Danfeng Hong, Bing Zhang, et al.. (2024). Interpretable foundation models as decryptors peering into the Earth system. The Innovation. 5(5). 100682–100682. 4 indexed citations
14.
Sarfraz, Muhammad Shahzad, et al.. (2024). EXNet: (2+1)D Extreme Xception Net for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 5159–5172. 16 indexed citations
15.
Li, Chenyu, et al.. (2024). Macro-level gender inequality and child health outcomes in China. Chinese Sociological Review. 57(2). 222–249.
16.
Li, Chenyu, et al.. (2023). NDARTS: A Differentiable Architecture Search Based on the Neumann Series. Algorithms. 16(12). 536–536.
17.
Li, Chenyu, Bing Zhang, Danfeng Hong, Jing Yao, & Jocelyn Chanussot. (2023). LRR-Net: An Interpretable Deep Unfolding Network for Hyperspectral Anomaly Detection. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–12. 214 indexed citations breakdown →
18.
Yao, Jing, Bing Zhang, Chenyu Li, Danfeng Hong, & Jocelyn Chanussot. (2023). Extended Vision Transformer (ExViT) for Land Use and Land Cover Classification: A Multimodal Deep Learning Framework. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–15. 254 indexed citations breakdown →
19.
Li, Chenyu, et al.. (2020). Super-Resolution for Hyperspectral Remote Sensing Images Based on the 3D Attention-SRGAN Network. Remote Sensing. 12(7). 1204–1204. 27 indexed citations
20.
Li, Chenyu, et al.. (2020). Block Sparse Bayesian Learning over Local Dictionary for Robust SAR Target Recognition. International Journal of Optics. 2020. 1–10. 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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