Renwei Dian

4.1k total citations · 4 hit papers
47 papers, 3.0k citations indexed

About

Renwei Dian is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Renwei Dian has authored 47 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Media Technology, 34 papers in Computer Vision and Pattern Recognition and 6 papers in Biomedical Engineering. Recurrent topics in Renwei Dian's work include Advanced Image Fusion Techniques (34 papers), Remote-Sensing Image Classification (25 papers) and Image and Signal Denoising Methods (24 papers). Renwei Dian is often cited by papers focused on Advanced Image Fusion Techniques (34 papers), Remote-Sensing Image Classification (25 papers) and Image and Signal Denoising Methods (24 papers). Renwei Dian collaborates with scholars based in China, Portugal and Germany. Renwei Dian's co-authors include Shutao Li, Leyuan Fang, Anjing Guo, José M. Bioucas‐Dias, Xudong Kang, Haibo Liu, Bin Sun, Jinyang Liu, Ting Lu and Qi Wei and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Renwei Dian

46 papers receiving 2.9k citations

Hit Papers

Fusing Hyperspectral and Multispectral Images via Coupled... 2018 2026 2020 2023 2018 2018 2019 2020 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
Renwei Dian China 21 2.5k 2.1k 279 219 189 47 3.0k
Lina Zhuang China 27 1.8k 0.7× 1.2k 0.6× 357 1.3× 195 0.9× 484 2.6× 61 2.4k
Xiangyong Cao China 23 1.3k 0.5× 1.3k 0.6× 178 0.6× 140 0.6× 283 1.5× 81 2.0k
Dacheng Tao China 14 830 0.3× 1.7k 0.8× 209 0.7× 79 0.4× 167 0.9× 18 2.1k
Jingxiang Yang China 18 1.8k 0.7× 1.1k 0.5× 175 0.6× 84 0.4× 596 3.2× 49 2.1k
Le Sun China 27 2.1k 0.8× 978 0.5× 233 0.8× 118 0.5× 1.1k 5.8× 117 2.6k
Weiying Xie China 32 2.2k 0.9× 1.1k 0.5× 152 0.5× 395 1.8× 775 4.1× 113 2.9k
Fengchao Xiong China 18 874 0.4× 588 0.3× 135 0.5× 214 1.0× 251 1.3× 56 1.1k
Houzhang Fang China 22 901 0.4× 1.1k 0.5× 298 1.1× 344 1.6× 41 0.2× 49 1.7k
Fulin Luo China 22 1.5k 0.6× 855 0.4× 122 0.4× 158 0.7× 760 4.0× 84 2.3k
Tsung‐Han Chan Taiwan 19 1.2k 0.5× 569 0.3× 359 1.3× 69 0.3× 485 2.6× 50 1.8k

Countries citing papers authored by Renwei Dian

Since Specialization
Citations

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

Fields of papers citing papers by Renwei Dian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renwei Dian

This figure shows the co-authorship network connecting the top 25 collaborators of Renwei Dian. A scholar is included among the top collaborators of Renwei Dian 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 Renwei Dian. Renwei Dian 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.
Guo, Shuo, et al.. (2025). Spatial Invertible Network With Mamba-Convolution for Hyperspectral Image Fusion. IEEE Journal of Selected Topics in Signal Processing. 19(8). 1643–1653. 1 indexed citations
2.
Liu, Jinyang, et al.. (2025). A Selective Re-Learning Mechanism for Hyperspectral Fusion Imaging. 7437–7446.
3.
Xie, Ting, et al.. (2024). Multishot Compressive Hyperspectral Imaging Based on Tensor Fibered Rank Minimization and Its Primal-Dual Algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 4466–4477. 2 indexed citations
4.
Kang, Xudong, et al.. (2024). Multi-Granularity Context Perception Network for Open Set Recognition of Camouflaged Objects. IEEE Transactions on Multimedia. 27. 2436–2449. 1 indexed citations
5.
Dian, Renwei, et al.. (2024). Hyperspectral Image Fusion via a Novel Generalized Tensor Nuclear Norm Regularization. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 7437–7448. 20 indexed citations
6.
Dian, Renwei, et al.. (2024). Spectral Super-Resolution via Deep Low-Rank Tensor Representation. IEEE Transactions on Neural Networks and Learning Systems. 36(3). 5140–5150. 30 indexed citations
7.
Liu, Jinyang, et al.. (2024). MDENet: Multidomain Differential Excavating Network for Remote Sensing Image Change Detection. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–11. 9 indexed citations
8.
Liu, Jinyang, et al.. (2024). Asymptotic Spectral Mapping for Hyperspectral Image Fusion. IEEE Transactions on Circuits and Systems for Video Technology. 35(4). 3475–3485. 1 indexed citations
9.
Liu, Jinyang, Shutao Li, L.B. Tan, & Renwei Dian. (2024). Denoiser Learning for Infrared and Visible Image Fusion. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 13470–13482. 2 indexed citations
10.
Bai, Minru, et al.. (2024). Subspace-based coupled tensor decomposition for hyperspectral blind fusion. Inverse Problems and Imaging. 19(3). 560–591. 1 indexed citations
11.
Dian, Renwei, et al.. (2024). Multistage Spatial-Spectral Fusion Network for Spectral Super-Resolution. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 12736–12746. 8 indexed citations
12.
Li, Shutao, Renwei Dian, & Haibo Liu. (2023). Learning the external and internal priors for multispectral and hyperspectral image fusion. Science China Information Sciences. 66(4). 39 indexed citations
13.
Guo, Anjing, et al.. (2023). Surface defect detection competition with a bio-inspired vision sensor. National Science Review. 10(6). nwad130–nwad130. 3 indexed citations
14.
Liu, Jinyang, et al.. (2023). Focus Relationship Perception for Unsupervised Multi-Focus Image Fusion. IEEE Transactions on Multimedia. 26. 6155–6165. 4 indexed citations
15.
Kang, Xudong, et al.. (2023). FSNet: Focus Scanning Network for Camouflaged Object Detection. IEEE Transactions on Image Processing. 32. 2267–2278. 47 indexed citations
16.
Song, Weiwei, Zhi Gao, Renwei Dian, et al.. (2022). Asymmetric Hash Code Learning for Remote Sensing Image Retrieval. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–14. 42 indexed citations
17.
Dian, Renwei, Shutao Li, Bin Sun, & Anjing Guo. (2020). Recent advances and new guidelines on hyperspectral and multispectral image fusion. Information Fusion. 69. 40–51. 186 indexed citations
18.
Dian, Renwei, Shutao Li, Leyuan Fang, & José M. Bioucas‐Dias. (2018). Hyperspectral Image Super-Resolution via Local Low-Rank and Sparse Representations. 4003–4006. 22 indexed citations
19.
Dian, Renwei, Leyuan Fang, & Shutao Li. (2017). Hyperspectral Image Super-Resolution via Non-local Sparse Tensor Factorization. 3862–3871. 247 indexed citations
20.
Dian, Renwei, Shutao Li, & Leyuan Fang. (2016). Non-local sparse representation for hyperspectral image super-resolution. 2832–2835. 6 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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